Sebastián Ramírez López - Academia.edu (original) (raw)
Papers by Sebastián Ramírez López
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Over the last years, convolutional neural networks (CNNs) have been widely used in remote sensing... more Over the last years, convolutional neural networks (CNNs) have been widely used in remote sensing applications, such as marine surveillance, traffic management, or road networks detection. However, since CNNs have extremely high computational, bandwith, and memory requirements, the hardware implementation of a CNN on space-grade devices like field-programmable gate array (FPGAs) for the on-board processing of the acquired images has brought many challenges, since the computational capabilities of the on-board hardware devices are limited. Hence, implementations have to be carefully planned. In this article, the authors present their work toward the implementation of an efficient CNN onto a space-grade FPGA in order to achieve the on-board processing of very-high resolution remotely sensed images as soon as the data are provided by the sensor. All this work has been conducted within the EU-funded Video Imaging Demonstrator for Earth Observation project. As it will be presented in this article, the work includes the introduction of a methodology based on the project constraints, the evaluation of different state-of-the-art CNN architectures by means of a new efficiency measurement also proposed in this work, the introduction of a new efficient CNN architecture, and finally, its optimized hardware implementation by means of high-level synthesis tools. The results obtained following the proposed methodology demonstrate that the uncovered architecture is able to detect targets of interest in RGB images with a much higher efficiency than state-of-the-art solutions, while requiring a much smaller amount of computing and memory resources.
Agronomy, 2021
This study provides the basis for implementing a continuous treatment system for wastewater conta... more This study provides the basis for implementing a continuous treatment system for wastewater containing a pesticide mixture formed by atrazine, iprodione, and chlorpyrifos. Two fungal strains (Verticilium sp. H5 and Metacordyceps sp. H12) isolated from a biomixture of a biopurification system were able to remove different pesticide concentrations (10 to 50 mg L−1) efficiently from the liquid medium; however, the half-life of the pesticides was reduced and characterized by a T1/2 of 5.4 to 9.2 d for atrazine, 3.7 to 5.8 d for iprodione, and 2.6 to 2.9 d for chlorpyrifos using the fungal consortium. The immobilization of the fungal consortium in alginate bead was effective, with the highest pesticide removal observed using an inoculum concentration of 30% wv−1. The packed-bed reactor with the immobilized fungal consortium, which was operated in the continuous mode at different flow rates (30, 60, and 90 mL h−1), required approximately 10 d to achieve removal efficiency (atrazine: 59%; ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Onboard data processing for on-the-fly decisionmaking applications has recently gained momentum i... more Onboard data processing for on-the-fly decisionmaking applications has recently gained momentum in the field of remote sensing. In this context, hyperspectral anomaly detection has received special attention since its main purpose lies in the identification of abnormal events in an unsupervised manner. Nevertheless, onboard real-time hyperspectral image processing still poses several challenges before becoming a reality. This is why there is an emerging trend toward the development of hardware-friendly algorithmic solutions embedded in reconfigurable devices. In this context, this work contributes to a hardware architecture that ensures a progressive line processing in time-sensitive applications limited by the scarcity of hardware resources. In this sense, we have implemented the state-of-the-art hardware-friendly line-by-line fast anomaly detector for hyperspectral imagery (HW-LbL-FAD) detector on a reconfigurable hardware for a real-time performance. Specifically, we have selected a cost-optimized field-programmable gate array (ZC7Z020-CLG484) to implement our solution whose results draw up a good tradeoff between the following three features: time performance, energy consumption, and cost. The experimental results indicate that our hardware component is able to process hyperspectral images of 825x1024 pixels and 160 bands in 0.51 s with a power budget of 1.3 W and costs around 150€. Regarding detection performance, the HW-LbL-FAD algorithm outperforms other state-of-the-art algorithms. Index Terms-Anomaly detection, field-programmable gate arrays (FPGAs), high-level synthesis (HLS), hyperspectral imaging, line-by-line performance, low power, real time. I. INTRODUCTION I N THE recent years, anomaly detection has been extensively studied in the field of hyperspectral data analysis [1]. Its Manuscript
Sensors, 2022
Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information ... more Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information in a broad set of applications in different domains, from precision agriculture to environmental science. A first step in the preparation of the algorithms to be employed outdoors starts at a laboratory level, capturing a high amount of samples to be analysed and processed in order to extract the necessary information about the spectral characteristics of the studied samples in the most precise way. In this article, a custom-made scanning system for hyperspectral image acquisition is described. Commercially available components have been carefully selected in order to be integrated into a flexible infrastructure able to obtain data from any Generic Interface for Cameras (GenICam) compliant devices using the gigabyte Ethernet interface. The entire setup has been tested using the Specim FX hyperspectral series (FX10 and FX17) and a Graphical User Interface (GUI) has been developed in order...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
The integration of video sensors on-board satellites is becoming a trend in the space industry, s... more The integration of video sensors on-board satellites is becoming a trend in the space industry, since they provide extra information in the temporal domain when compared with traditional remote sensing imaging acquisition equipment. The inclusion of the temporal dimension together with the constant increase in the sensor resolution supposes a challenge for on-board processing, taking into account the limited computational and storage resources on-board satellites and that it is unfeasible to directly transmit raw video to ground, due to downlink bandwidth limitations. For these reasons, on-board video compression is needed. However, the inherent complexity of the video encoders used on ground limits their implementation on environments with high constraints in terms of computational burden, area, and power consumption. This article proposes an extended compression chain that implements as compression core the CCSDS 123.0-B-2 standard, originally developed for near-lossless compression of multi-and hyperspectral images. In addition, some preprocessing stages are included to manage the temporal dimension of RGB videos efficiently. The proposed solution guarantees low complexity and flexibility to compress both multi-and hyperspectral images and panchromatic and RGB videos by using a single compression instance, which is adapted by adding or removing the appropriate stages. Results demonstrate the viability of this solution to be implemented on space payloads, since high compression ratios are achieved without incurring in a penalty in terms of video quality. Index Terms-Consultative committee for space data systems (CCSDS), multispectral imaging, on-board processing, space missions, video compression.
Remote Sensing, 2020
Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power bu... more Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power budget and low-bandwidth downlinks. Therefore, handling hyperspectral data in this context can jeopardize the operational time of the system. FPGAs have been traditionally regarded as the most power-efficient computing platforms. However, there is little experimental evidence to support this claim, which is especially critical since the actual behavior of the solutions based on reconfigurable technology is highly dependent on the type of application. In this work, a highly optimized implementation of an FPGA accelerator of the novel HyperLCA algorithm has been developed and thoughtfully analyzed in terms of performance and power efficiency. In this regard, a modification of the aforementioned lossy compression solution has also been proposed to be efficiently executed into FPGA devices using fixed-point arithmetic. Single and multi-core versions of the reconfigurable computing platforms ar...
Remote Sensing, 2021
Hyperspectral sensors that are mounted in unmanned aerial vehicles (UAVs) offer many benefits for... more Hyperspectral sensors that are mounted in unmanned aerial vehicles (UAVs) offer many benefits for different remote sensing applications by combining the capacity of acquiring a high amount of information that allows for distinguishing or identifying different materials, and the flexibility of the UAVs for planning different kind of flying missions. However, further developments are still needed to take advantage of the combination of these technologies for applications that require a supervised or semi-supervised process, such as defense, surveillance, or search and rescue missions. The main reason is that, in these scenarios, the acquired data typically need to be rapidly transferred to a ground station where it can be processed and/or visualized in real-time by an operator for taking decisions on the fly. This is a very challenging task due to the high acquisition data rate of the hyperspectral sensors and the limited transmission bandwidth. This research focuses on providing a wo...
Electronics, 2020
This paper describes a novel hardware implementation of a lossy multispectral and hyperspectral i... more This paper describes a novel hardware implementation of a lossy multispectral and hyperspectral image compressor for on-board operation in space missions. The compression algorithm is a lossy extension of the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-1 lossless standard that includes a bit-rate control stage, which in turn manages the losses the compressor may introduce to achieve higher compression ratios without compromising the recovered image quality. The algorithm has been implemented using High-Level Synthesis (HLS) techniques to increase design productivity by raising the abstraction level. The proposed lossy compression solution is deployed onto ARTICo3, a dynamically reconfigurable multi-accelerator architecture, obtaining a run-time adaptive solution that enables user-selectable performance (i.e., load more hardware accelerators to transparently increase throughput), power consumption, and fault tolerance (i.e., group hardware accelerators to transparen...
Remote Sensing, 2020
The on-board processing of remotely sensed hyperspectral images is gaining momentum for applicati... more The on-board processing of remotely sensed hyperspectral images is gaining momentum for applications that demand a quick response as an alternative to conventional approaches where the acquired images are off-line processed once they have been transmitted to the ground segment. However, the adoption of this on-board processing strategy brings further challenges for the remote-sensing research community due to the high data rate of the new-generation hyperspectral sensors and the limited amount of available on-board computational resources. This situation becomes even more stringent when different time-sensitive applications coexist, since different tasks must be sequentially processed onto the same computing device. In this work, we have dealt with this issue through the definition of a set of core operations that extracts spectral features useful for many hyperspectral analysis techniques, such as unmixing, compression and target/anomaly detection. Accordingly, it permits the concu...
Remote Sensing, 2018
Hyperspectral sensors are able to provide information that is useful for many different applicati... more Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth's surface. In this situation, an efficient compression of the hyperspectral images is mandatory in order to save bandwidth and storage space. Lossless compression algorithms have been traditionally preferred, in order to preserve all the information present in the hyperspectral cube for scientific purposes, despite their limited compression ratio. Nevertheless, the increment in the data-rate of the new-generation sensors is making more critical the necessity of obtaining higher compression ratios, making it necessary to use lossy compression techniques. A new transform-based lossy compression algorithm, namely Lossy Compression Algorithm for Hyperspectral Image Systems (HyperLCA), is proposed in this manuscript. This compressor has been developed for achieving high compression ratios with a good compression performance at a reasonable computational burden. An extensive amount of experiments have been performed in order to evaluate the goodness of the proposed HyperLCA compressor using different calibrated and uncalibrated hyperspectral images from the AVIRIS and Hyperion sensors. The results provided by the proposed HyperLCA compressor have been evaluated and compared against those produced by the most relevant state-of-the-art compression solutions. The theoretical and experimental evidence indicates that the proposed algorithm represents an excellent option for lossy compressing hyperspectral images, especially for applications where the available computational resources are limited, such as on-board scenarios.
Remote Sensing, 2018
Space missions are facing disruptive innovation since the appearance of small, lightweight, and l... more Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computing power. To face this change, the on-board processing paradigm is advancing towards the clustering of satellites, and moving to distributed and collaborative schemes in order to maintain acceptable performance levels in complex applications such as hyperspectral image processing. In this scenario, hybrid hardware/software and reconfigurable computing have appeared as key enabling technologies, even though they increase complexity in both design and run time. In this paper, the ARTICo3 framework, which abstracts and eases the design and run-time management of hardware-accelerated systems, has been used to deploy a networked implementation of the Fast UNmixing (FUN) algorithm, which performs linear unmixing of hyperspectral images in a sma...
SPIE Proceedings, 2016
Most practical hyperspectral anomaly detection (AD) applications require real-time processing for... more Most practical hyperspectral anomaly detection (AD) applications require real-time processing for detecting complex targets from their background. This is especially critical in defense and surveillance domains, but also in many other scenarios, in which a rapid response is mandatory to save human lives. Dealing with such a high dimensionality of data requires the conception of new algorithms to ease the demanding computing performance. Pushbroom scanning represents the mainstream in hyperspectral imaging, introducing added complexity to the equation as there is no information of future pixels. In this paper, a novel technique named line-by-line anomaly detection (LbL-AD) algorithm, is presented as a way of performing real-time processing with a push-broom sensor. The sensor has been mounted on an unmanned aerial vehicle, and the acquired images, together with others from the scientific literature and synthetic ones, have been used to extensively validate the proposed algorithm in terms of accuracy, based on different metrics and processing time. Comparisons with state-of-the-art algorithms were accomplished in order to evaluate the goodness of the LbL-AD, giving as a result an outstanding performance. Index Terms-Anomaly detection (AD), hyperspectral imagery, onboard processing, push-broom sensor, unmanned aerial vehicle (UAV).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013
One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the prese... more One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the presence of mixed pixels, which arise when the spatial resolution of the sensor is not able to separate spectrally distinct materials. Due to this reason, spectral unmixing has become one of the most important tasks for hyperspectral data exploitation. However, unmixing algorithms can be computationally very expensive, a fact that compromises their use in applications under real-time constraints. For this purpose, in this paper we develop two efficient implementations of a full hyperspectral unmixing chain on two different kinds of high performance computing architectures: graphics processing units (GPUs) and multi-core processors. The proposed full unmixing chain is composed for three stages: (i) estimation of the number of pure spectral signatures or endmembers, (ii) automatic identification of the estimated endmembers, and (iii) estimation of the fractional abundance of each endmember in each pixel of the scene. The two computing platforms used in this work are inter-compared in the context of hyperspectral unmixing applications. The GPU implementation of the proposed methodology has been implemented using the compute devide unified architecture (CUDA) and the cuBLAS library, and tested on two different GPU architectures: NVidia™ GeForce GTX 580 and NVidia™ Tesla C1060. It provides real-time unmixing performance in two different analysis scenarios using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada and the World Trade Center complex in New York City. The multi-core implementation, developed using the applications program interface (API) OpenMP and the Intel Math Kernel Library (MKL) used for matrix multiplications, achieved near real-time performance in the same scenarios. A comparison of both architectures in terms of performance, cost and mission payload considerations is given based on the results obtained in the two considered data analysis scenarios.
Designers' Forum: Design, Automation and Test in Europe Conference and Exhibition, 2005
Motion estimation is the most critical process in video coding systems. First of all, it has a de... more Motion estimation is the most critical process in video coding systems. First of all, it has a definitive impact on the rate-distortion performance given by the video encoder. Secondly, it is the most computationally intensive process within the encoding loop. For these reasons, the design of high-performance low-cost motion estimators is a crucial task in the video compression field. An adaptive cost block matching (ACBM) motion estimation technique is presented in this paper, featuring an excellent tradeoff between the quality of the reconstructed video sequences and the computational effort. Simulation results demonstrate that the ACBM algorithm achieves a slight better rate-distortion performance than the one given by the well-known full search algorithm block matching algorithm with reductions of up to 95% in the computational load.
International Journal of Parallel Programming, 2012
A novel high throughput and scalable unified architecture for the computation of the transform op... more A novel high throughput and scalable unified architecture for the computation of the transform operations in video codecs for advanced standards is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute all the two-dimensional 4 × 4 and 2 × 2 transforms of the H.264/AVC standard. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-5 FPGA demonstrated the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area relatively higher than other similar recently published designs targeting the H.264/AVC standard. Such results also showed that, when integrated in a multi-core embedded system, this architecture provides speedup factors of about 120× concerning pure software implementations of the transform algorithms, T. Dias (B)
2011 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, 2011
An innovative high throughput and scalable multitransform architecture for H.264/AVC is presented... more An innovative high throughput and scalable multitransform architecture for H.264/AVC is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute the 4×4 forward/inverse integer DCT, as well as the 2-D 4 × 4 / 2 × 2 Hadamard transforms. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-4 FPGA demonstrate the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area at least 1.8× higher than other similar recently published designs. Furthermore, such results also showed that this architecture can compute, in realtime, all the above mentioned H.264/AVC transforms for video sequences with resolutions up to UHDV.
2011 IEEE 17th International Conference on Parallel and Distributed Systems, 2011
Onboard processing of remotely sensed hyperspectral data is a highly desirable goal in many appli... more Onboard processing of remotely sensed hyperspectral data is a highly desirable goal in many applications. For this purpose, compact reconfigurable hardware modules such as field programmable gate arrays (FPGAs) are widely used. In this paper, we develop a new implementation of an automatic target generation process (ATGP) for hyperspectral images. Our implementation is based on a design methodology that starts from a high-level description in Matlab (or alternative C/C++) and obtains a register transfer level (RTL) description that can be ported to FPGAs. In order to validate our new implementation, we develop a quantitative and comparative study using two different FPGA architectures: Xilinx Virtex-5 and Altera Stratix-III Altera. Experimental results have been obtained in the context of a real application focused on the detection of mineral components over the Cuprite mining district (Nevada), using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Our experimental results indicate that the proposed implementation can achieve peak frequency designs above 200MHz in the considered FPGAs, in addition to satisfactory results in terms of target detection accuracy and parallel performance. This represents a step forward towards the design of real-time onboard implementations of hyperspectral image analysis algorithms.
Anàlisi, 2012
Los medios de comunicación desempeñan un papel relevante en la sociedad, especialmente a la hora ... more Los medios de comunicación desempeñan un papel relevante en la sociedad, especialmente a la hora de abordar y presentar el discurso político. La clase política en general es una de las principales fuentes de información periodística al igual que cualquier tipo de movimiento que ésta realice. A ello hay que sumar un alejamiento de la objetividad que tienen los principales medios de comunicación españoles, cuestión que los hace partícipes de una visión subjetiva y posicionada cuando se aborda la información política. En este trabajo, presentamos un ejemplo de cómo dos diarios de referencia españoles, El País y El Mundo, elaboran informaciones sobre las elecciones europeas de 2009 en las que la política nacional, salpicada por diferentes escándalos y procesos negativos, evidencia un espíritu de confrontación general que se manifiesta en partidismo mediático y polarizado al mismo tiempo que un negativismo político.
Proceedings of the IEEE, 2013
Fast processing solutions for compression and/or interpretation of hyperspectral data onboard spa... more Fast processing solutions for compression and/or interpretation of hyperspectral data onboard spacecraft imaging platforms are discussed in this paper with the purpose of giving a more efficient exploitation of hyperspectral data sets in various applications.
IEEE Transactions on Consumer Electronics, 2011
A new high throughput and scalable architecture for unified transform coding in H.264/AVC is prop... more A new high throughput and scalable architecture for unified transform coding in H.264/AVC is proposed in this paper. Such flexible structure is capable of computing all the 4x4 and 2x2 transforms for Ultra High Definition Video (UHDV) applications (4320x7680@ 30fps) in real-time and with low hardware cost. These significantly high performance levels were proven with the implementation of several different configurations of the proposed structure using both FPGA and ASIC 90 nm technologies. In addition, such experimental evaluation also demonstrated the high area efficiency of theproposed architecture, which in terms of Data Throughput per Unit of Area (DTUA) is at least 1.5 times more efficient than its more prominent related designs(1).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Over the last years, convolutional neural networks (CNNs) have been widely used in remote sensing... more Over the last years, convolutional neural networks (CNNs) have been widely used in remote sensing applications, such as marine surveillance, traffic management, or road networks detection. However, since CNNs have extremely high computational, bandwith, and memory requirements, the hardware implementation of a CNN on space-grade devices like field-programmable gate array (FPGAs) for the on-board processing of the acquired images has brought many challenges, since the computational capabilities of the on-board hardware devices are limited. Hence, implementations have to be carefully planned. In this article, the authors present their work toward the implementation of an efficient CNN onto a space-grade FPGA in order to achieve the on-board processing of very-high resolution remotely sensed images as soon as the data are provided by the sensor. All this work has been conducted within the EU-funded Video Imaging Demonstrator for Earth Observation project. As it will be presented in this article, the work includes the introduction of a methodology based on the project constraints, the evaluation of different state-of-the-art CNN architectures by means of a new efficiency measurement also proposed in this work, the introduction of a new efficient CNN architecture, and finally, its optimized hardware implementation by means of high-level synthesis tools. The results obtained following the proposed methodology demonstrate that the uncovered architecture is able to detect targets of interest in RGB images with a much higher efficiency than state-of-the-art solutions, while requiring a much smaller amount of computing and memory resources.
Agronomy, 2021
This study provides the basis for implementing a continuous treatment system for wastewater conta... more This study provides the basis for implementing a continuous treatment system for wastewater containing a pesticide mixture formed by atrazine, iprodione, and chlorpyrifos. Two fungal strains (Verticilium sp. H5 and Metacordyceps sp. H12) isolated from a biomixture of a biopurification system were able to remove different pesticide concentrations (10 to 50 mg L−1) efficiently from the liquid medium; however, the half-life of the pesticides was reduced and characterized by a T1/2 of 5.4 to 9.2 d for atrazine, 3.7 to 5.8 d for iprodione, and 2.6 to 2.9 d for chlorpyrifos using the fungal consortium. The immobilization of the fungal consortium in alginate bead was effective, with the highest pesticide removal observed using an inoculum concentration of 30% wv−1. The packed-bed reactor with the immobilized fungal consortium, which was operated in the continuous mode at different flow rates (30, 60, and 90 mL h−1), required approximately 10 d to achieve removal efficiency (atrazine: 59%; ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Onboard data processing for on-the-fly decisionmaking applications has recently gained momentum i... more Onboard data processing for on-the-fly decisionmaking applications has recently gained momentum in the field of remote sensing. In this context, hyperspectral anomaly detection has received special attention since its main purpose lies in the identification of abnormal events in an unsupervised manner. Nevertheless, onboard real-time hyperspectral image processing still poses several challenges before becoming a reality. This is why there is an emerging trend toward the development of hardware-friendly algorithmic solutions embedded in reconfigurable devices. In this context, this work contributes to a hardware architecture that ensures a progressive line processing in time-sensitive applications limited by the scarcity of hardware resources. In this sense, we have implemented the state-of-the-art hardware-friendly line-by-line fast anomaly detector for hyperspectral imagery (HW-LbL-FAD) detector on a reconfigurable hardware for a real-time performance. Specifically, we have selected a cost-optimized field-programmable gate array (ZC7Z020-CLG484) to implement our solution whose results draw up a good tradeoff between the following three features: time performance, energy consumption, and cost. The experimental results indicate that our hardware component is able to process hyperspectral images of 825x1024 pixels and 160 bands in 0.51 s with a power budget of 1.3 W and costs around 150€. Regarding detection performance, the HW-LbL-FAD algorithm outperforms other state-of-the-art algorithms. Index Terms-Anomaly detection, field-programmable gate arrays (FPGAs), high-level synthesis (HLS), hyperspectral imaging, line-by-line performance, low power, real time. I. INTRODUCTION I N THE recent years, anomaly detection has been extensively studied in the field of hyperspectral data analysis [1]. Its Manuscript
Sensors, 2022
Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information ... more Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information in a broad set of applications in different domains, from precision agriculture to environmental science. A first step in the preparation of the algorithms to be employed outdoors starts at a laboratory level, capturing a high amount of samples to be analysed and processed in order to extract the necessary information about the spectral characteristics of the studied samples in the most precise way. In this article, a custom-made scanning system for hyperspectral image acquisition is described. Commercially available components have been carefully selected in order to be integrated into a flexible infrastructure able to obtain data from any Generic Interface for Cameras (GenICam) compliant devices using the gigabyte Ethernet interface. The entire setup has been tested using the Specim FX hyperspectral series (FX10 and FX17) and a Graphical User Interface (GUI) has been developed in order...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
The integration of video sensors on-board satellites is becoming a trend in the space industry, s... more The integration of video sensors on-board satellites is becoming a trend in the space industry, since they provide extra information in the temporal domain when compared with traditional remote sensing imaging acquisition equipment. The inclusion of the temporal dimension together with the constant increase in the sensor resolution supposes a challenge for on-board processing, taking into account the limited computational and storage resources on-board satellites and that it is unfeasible to directly transmit raw video to ground, due to downlink bandwidth limitations. For these reasons, on-board video compression is needed. However, the inherent complexity of the video encoders used on ground limits their implementation on environments with high constraints in terms of computational burden, area, and power consumption. This article proposes an extended compression chain that implements as compression core the CCSDS 123.0-B-2 standard, originally developed for near-lossless compression of multi-and hyperspectral images. In addition, some preprocessing stages are included to manage the temporal dimension of RGB videos efficiently. The proposed solution guarantees low complexity and flexibility to compress both multi-and hyperspectral images and panchromatic and RGB videos by using a single compression instance, which is adapted by adding or removing the appropriate stages. Results demonstrate the viability of this solution to be implemented on space payloads, since high compression ratios are achieved without incurring in a penalty in terms of video quality. Index Terms-Consultative committee for space data systems (CCSDS), multispectral imaging, on-board processing, space missions, video compression.
Remote Sensing, 2020
Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power bu... more Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power budget and low-bandwidth downlinks. Therefore, handling hyperspectral data in this context can jeopardize the operational time of the system. FPGAs have been traditionally regarded as the most power-efficient computing platforms. However, there is little experimental evidence to support this claim, which is especially critical since the actual behavior of the solutions based on reconfigurable technology is highly dependent on the type of application. In this work, a highly optimized implementation of an FPGA accelerator of the novel HyperLCA algorithm has been developed and thoughtfully analyzed in terms of performance and power efficiency. In this regard, a modification of the aforementioned lossy compression solution has also been proposed to be efficiently executed into FPGA devices using fixed-point arithmetic. Single and multi-core versions of the reconfigurable computing platforms ar...
Remote Sensing, 2021
Hyperspectral sensors that are mounted in unmanned aerial vehicles (UAVs) offer many benefits for... more Hyperspectral sensors that are mounted in unmanned aerial vehicles (UAVs) offer many benefits for different remote sensing applications by combining the capacity of acquiring a high amount of information that allows for distinguishing or identifying different materials, and the flexibility of the UAVs for planning different kind of flying missions. However, further developments are still needed to take advantage of the combination of these technologies for applications that require a supervised or semi-supervised process, such as defense, surveillance, or search and rescue missions. The main reason is that, in these scenarios, the acquired data typically need to be rapidly transferred to a ground station where it can be processed and/or visualized in real-time by an operator for taking decisions on the fly. This is a very challenging task due to the high acquisition data rate of the hyperspectral sensors and the limited transmission bandwidth. This research focuses on providing a wo...
Electronics, 2020
This paper describes a novel hardware implementation of a lossy multispectral and hyperspectral i... more This paper describes a novel hardware implementation of a lossy multispectral and hyperspectral image compressor for on-board operation in space missions. The compression algorithm is a lossy extension of the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-1 lossless standard that includes a bit-rate control stage, which in turn manages the losses the compressor may introduce to achieve higher compression ratios without compromising the recovered image quality. The algorithm has been implemented using High-Level Synthesis (HLS) techniques to increase design productivity by raising the abstraction level. The proposed lossy compression solution is deployed onto ARTICo3, a dynamically reconfigurable multi-accelerator architecture, obtaining a run-time adaptive solution that enables user-selectable performance (i.e., load more hardware accelerators to transparently increase throughput), power consumption, and fault tolerance (i.e., group hardware accelerators to transparen...
Remote Sensing, 2020
The on-board processing of remotely sensed hyperspectral images is gaining momentum for applicati... more The on-board processing of remotely sensed hyperspectral images is gaining momentum for applications that demand a quick response as an alternative to conventional approaches where the acquired images are off-line processed once they have been transmitted to the ground segment. However, the adoption of this on-board processing strategy brings further challenges for the remote-sensing research community due to the high data rate of the new-generation hyperspectral sensors and the limited amount of available on-board computational resources. This situation becomes even more stringent when different time-sensitive applications coexist, since different tasks must be sequentially processed onto the same computing device. In this work, we have dealt with this issue through the definition of a set of core operations that extracts spectral features useful for many hyperspectral analysis techniques, such as unmixing, compression and target/anomaly detection. Accordingly, it permits the concu...
Remote Sensing, 2018
Hyperspectral sensors are able to provide information that is useful for many different applicati... more Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth's surface. In this situation, an efficient compression of the hyperspectral images is mandatory in order to save bandwidth and storage space. Lossless compression algorithms have been traditionally preferred, in order to preserve all the information present in the hyperspectral cube for scientific purposes, despite their limited compression ratio. Nevertheless, the increment in the data-rate of the new-generation sensors is making more critical the necessity of obtaining higher compression ratios, making it necessary to use lossy compression techniques. A new transform-based lossy compression algorithm, namely Lossy Compression Algorithm for Hyperspectral Image Systems (HyperLCA), is proposed in this manuscript. This compressor has been developed for achieving high compression ratios with a good compression performance at a reasonable computational burden. An extensive amount of experiments have been performed in order to evaluate the goodness of the proposed HyperLCA compressor using different calibrated and uncalibrated hyperspectral images from the AVIRIS and Hyperion sensors. The results provided by the proposed HyperLCA compressor have been evaluated and compared against those produced by the most relevant state-of-the-art compression solutions. The theoretical and experimental evidence indicates that the proposed algorithm represents an excellent option for lossy compressing hyperspectral images, especially for applications where the available computational resources are limited, such as on-board scenarios.
Remote Sensing, 2018
Space missions are facing disruptive innovation since the appearance of small, lightweight, and l... more Space missions are facing disruptive innovation since the appearance of small, lightweight, and low-cost satellites (e.g., CubeSats). The use of commercial devices and their limitations in cost usually entail a decrease in available on-board computing power. To face this change, the on-board processing paradigm is advancing towards the clustering of satellites, and moving to distributed and collaborative schemes in order to maintain acceptable performance levels in complex applications such as hyperspectral image processing. In this scenario, hybrid hardware/software and reconfigurable computing have appeared as key enabling technologies, even though they increase complexity in both design and run time. In this paper, the ARTICo3 framework, which abstracts and eases the design and run-time management of hardware-accelerated systems, has been used to deploy a networked implementation of the Fast UNmixing (FUN) algorithm, which performs linear unmixing of hyperspectral images in a sma...
SPIE Proceedings, 2016
Most practical hyperspectral anomaly detection (AD) applications require real-time processing for... more Most practical hyperspectral anomaly detection (AD) applications require real-time processing for detecting complex targets from their background. This is especially critical in defense and surveillance domains, but also in many other scenarios, in which a rapid response is mandatory to save human lives. Dealing with such a high dimensionality of data requires the conception of new algorithms to ease the demanding computing performance. Pushbroom scanning represents the mainstream in hyperspectral imaging, introducing added complexity to the equation as there is no information of future pixels. In this paper, a novel technique named line-by-line anomaly detection (LbL-AD) algorithm, is presented as a way of performing real-time processing with a push-broom sensor. The sensor has been mounted on an unmanned aerial vehicle, and the acquired images, together with others from the scientific literature and synthetic ones, have been used to extensively validate the proposed algorithm in terms of accuracy, based on different metrics and processing time. Comparisons with state-of-the-art algorithms were accomplished in order to evaluate the goodness of the LbL-AD, giving as a result an outstanding performance. Index Terms-Anomaly detection (AD), hyperspectral imagery, onboard processing, push-broom sensor, unmanned aerial vehicle (UAV).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013
One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the prese... more One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the presence of mixed pixels, which arise when the spatial resolution of the sensor is not able to separate spectrally distinct materials. Due to this reason, spectral unmixing has become one of the most important tasks for hyperspectral data exploitation. However, unmixing algorithms can be computationally very expensive, a fact that compromises their use in applications under real-time constraints. For this purpose, in this paper we develop two efficient implementations of a full hyperspectral unmixing chain on two different kinds of high performance computing architectures: graphics processing units (GPUs) and multi-core processors. The proposed full unmixing chain is composed for three stages: (i) estimation of the number of pure spectral signatures or endmembers, (ii) automatic identification of the estimated endmembers, and (iii) estimation of the fractional abundance of each endmember in each pixel of the scene. The two computing platforms used in this work are inter-compared in the context of hyperspectral unmixing applications. The GPU implementation of the proposed methodology has been implemented using the compute devide unified architecture (CUDA) and the cuBLAS library, and tested on two different GPU architectures: NVidia™ GeForce GTX 580 and NVidia™ Tesla C1060. It provides real-time unmixing performance in two different analysis scenarios using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada and the World Trade Center complex in New York City. The multi-core implementation, developed using the applications program interface (API) OpenMP and the Intel Math Kernel Library (MKL) used for matrix multiplications, achieved near real-time performance in the same scenarios. A comparison of both architectures in terms of performance, cost and mission payload considerations is given based on the results obtained in the two considered data analysis scenarios.
Designers' Forum: Design, Automation and Test in Europe Conference and Exhibition, 2005
Motion estimation is the most critical process in video coding systems. First of all, it has a de... more Motion estimation is the most critical process in video coding systems. First of all, it has a definitive impact on the rate-distortion performance given by the video encoder. Secondly, it is the most computationally intensive process within the encoding loop. For these reasons, the design of high-performance low-cost motion estimators is a crucial task in the video compression field. An adaptive cost block matching (ACBM) motion estimation technique is presented in this paper, featuring an excellent tradeoff between the quality of the reconstructed video sequences and the computational effort. Simulation results demonstrate that the ACBM algorithm achieves a slight better rate-distortion performance than the one given by the well-known full search algorithm block matching algorithm with reductions of up to 95% in the computational load.
International Journal of Parallel Programming, 2012
A novel high throughput and scalable unified architecture for the computation of the transform op... more A novel high throughput and scalable unified architecture for the computation of the transform operations in video codecs for advanced standards is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute all the two-dimensional 4 × 4 and 2 × 2 transforms of the H.264/AVC standard. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-5 FPGA demonstrated the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area relatively higher than other similar recently published designs targeting the H.264/AVC standard. Such results also showed that, when integrated in a multi-core embedded system, this architecture provides speedup factors of about 120× concerning pure software implementations of the transform algorithms, T. Dias (B)
2011 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, 2011
An innovative high throughput and scalable multitransform architecture for H.264/AVC is presented... more An innovative high throughput and scalable multitransform architecture for H.264/AVC is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute the 4×4 forward/inverse integer DCT, as well as the 2-D 4 × 4 / 2 × 2 Hadamard transforms. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-4 FPGA demonstrate the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area at least 1.8× higher than other similar recently published designs. Furthermore, such results also showed that this architecture can compute, in realtime, all the above mentioned H.264/AVC transforms for video sequences with resolutions up to UHDV.
2011 IEEE 17th International Conference on Parallel and Distributed Systems, 2011
Onboard processing of remotely sensed hyperspectral data is a highly desirable goal in many appli... more Onboard processing of remotely sensed hyperspectral data is a highly desirable goal in many applications. For this purpose, compact reconfigurable hardware modules such as field programmable gate arrays (FPGAs) are widely used. In this paper, we develop a new implementation of an automatic target generation process (ATGP) for hyperspectral images. Our implementation is based on a design methodology that starts from a high-level description in Matlab (or alternative C/C++) and obtains a register transfer level (RTL) description that can be ported to FPGAs. In order to validate our new implementation, we develop a quantitative and comparative study using two different FPGA architectures: Xilinx Virtex-5 and Altera Stratix-III Altera. Experimental results have been obtained in the context of a real application focused on the detection of mineral components over the Cuprite mining district (Nevada), using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Our experimental results indicate that the proposed implementation can achieve peak frequency designs above 200MHz in the considered FPGAs, in addition to satisfactory results in terms of target detection accuracy and parallel performance. This represents a step forward towards the design of real-time onboard implementations of hyperspectral image analysis algorithms.
Anàlisi, 2012
Los medios de comunicación desempeñan un papel relevante en la sociedad, especialmente a la hora ... more Los medios de comunicación desempeñan un papel relevante en la sociedad, especialmente a la hora de abordar y presentar el discurso político. La clase política en general es una de las principales fuentes de información periodística al igual que cualquier tipo de movimiento que ésta realice. A ello hay que sumar un alejamiento de la objetividad que tienen los principales medios de comunicación españoles, cuestión que los hace partícipes de una visión subjetiva y posicionada cuando se aborda la información política. En este trabajo, presentamos un ejemplo de cómo dos diarios de referencia españoles, El País y El Mundo, elaboran informaciones sobre las elecciones europeas de 2009 en las que la política nacional, salpicada por diferentes escándalos y procesos negativos, evidencia un espíritu de confrontación general que se manifiesta en partidismo mediático y polarizado al mismo tiempo que un negativismo político.
Proceedings of the IEEE, 2013
Fast processing solutions for compression and/or interpretation of hyperspectral data onboard spa... more Fast processing solutions for compression and/or interpretation of hyperspectral data onboard spacecraft imaging platforms are discussed in this paper with the purpose of giving a more efficient exploitation of hyperspectral data sets in various applications.
IEEE Transactions on Consumer Electronics, 2011
A new high throughput and scalable architecture for unified transform coding in H.264/AVC is prop... more A new high throughput and scalable architecture for unified transform coding in H.264/AVC is proposed in this paper. Such flexible structure is capable of computing all the 4x4 and 2x2 transforms for Ultra High Definition Video (UHDV) applications (4320x7680@ 30fps) in real-time and with low hardware cost. These significantly high performance levels were proven with the implementation of several different configurations of the proposed structure using both FPGA and ASIC 90 nm technologies. In addition, such experimental evaluation also demonstrated the high area efficiency of theproposed architecture, which in terms of Data Throughput per Unit of Area (DTUA) is at least 1.5 times more efficient than its more prominent related designs(1).