Merav Huber-Lerner | Ben Gurion University of the Negev (original) (raw)
Papers by Merav Huber-Lerner
SPIE Proceedings, 1999
ABSTRACT One result of the recent advances in different components of imaging systems technology ... more ABSTRACT One result of the recent advances in different components of imaging systems technology is that, these systems have become more resolution-limited and less noise-limited. The most useful tool utilized in characterization of resolution-limited systems is the ...
Applied Optics, 2016
Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of... more Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow-moving point targets that are less than one pixel in size, such as aircraft at long range from a sensor. Since transmitting IR imagery sequences to a base unit or storing them consumes considerable time and resources, a compression method that maintains the point target detection capabilities is highly desirable. In this work, we introduce a new parametric temporal compression that incorporates Gaussian fit and polynomial fit. We then proceed to spatial compression by spatially applying the lowest possible number of bits for representing each parameter over the parameters extracted by temporal compression, which is followed by bit encoding to achieve an end-to-end compression process of the sequence for data storage and transmission. We evaluate the proposed compression method using the variance estimation ratio score (VERS), which is a signal-to-noise ratio (SNR)-based measure for point target detection that scores each pixel and yields an SNR scores image. A high pixel score indicates that a target is suspected to traverse the pixel. From this score image we calculate the movie scores, which are found to be close to those of the original sequences. Furthermore, we present a new algorithm for automatic detection of the target tracks. This algorithm extracts the target location from the SNR scores image, which is acquired during the evaluation process, using Hough transform. This algorithm yields a similar detection probability (PD) and false alarm probability (PFA) of the compressed sequences and the original sequences. The parameters of the new parametric temporal compression successfully differentiate the targets from the background, yielding high PDs (above 83%) with low PFAs (below 0.043%) without the need to calculate pixel scores or to apply automatic detection of the target tracks.
Optical Engineering, 2001
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
2006 International Conference on Information Technology: Research and Education, 2006
... Ron Shmueli(b), Ofer Hadar(a), Revital Huber(a), Masha Maltz(c) Merav Huber(a) ... The percei... more ... Ron Shmueli(b), Ofer Hadar(a), Revital Huber(a), Masha Maltz(c) Merav Huber(a) ... The perceived visual information is affected by the network in a different manner than data or voice services [1]. Measuring and modeling networks capabilities with relation to visual information is ...
2006 International Conference on Information Technology: Research and Education, 2006
ABSTRACT
Signal and Data Processing of Small Targets 2013, 2013
ABSTRACT Infrared (IR) imagery sequences are commonly used for detecting moving targets in the pr... more ABSTRACT Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. The target detection performance is measured via the variance estimation ratio score (VERS), which essentially calculates the pixel scores of the sequences, where a high score indicates a target is suspected to traverse the pixel. VERS uses two parameters - long and short term windows, which were predetermined individually for each movie, depending on the target velocity and on the clouds intensity and amount, as opposed to clear sky (noise), in the background. In this work, we examine the correlation between the sequences' spatial and temporal features and these two windows. In addition, we modify VERS calculation, to enhance target detection and decrease cloud-edge scores and false detection. We conclude this work by evaluating VERS as a detection measure, using its original version and its modified version. The test sequences are both original real IR sequences as well as their relative compressed sequences using our designated temporal DCT quantization method.
Optical Engineering, 2004
We evaluate the degradation in a video sequence that suffers from increasing packet loss ratio (P... more We evaluate the degradation in a video sequence that suffers from increasing packet loss ratio (PLR), by using several kinds of quality measures, namely, mean square error (MSE); (the root MSE, which is weighted by the maximum signal change between pairs of pixelsthe ...
Optical Engineering, 2006
We analyze the connection between viewer-perceived quality and encoding schemes. The encoding sch... more We analyze the connection between viewer-perceived quality and encoding schemes. The encoding schemes depend on transmission bit-rate, MPEG compression depth, frame size and frame rate in a constant bit-rate (CBR) video transmission of a MPEG-2 video sequence. The ...
IEEE Transactions on Broadcasting, 2000
We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP net... more We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP network with a quality of service mechanism. The parameters of the encoding schemes include the transmission bit rate, the compression depth, the frame size and the frame rate. We demonstrate that when jointly considering the impact of the coding bit rate, the packet loss ratio and the video characteristics, we can identify an optimal encoding scheme that maximizes viewer-perceived quality. The video content, the compression and the transmission are represented by a vector which contains parameters. Based on subjective tests, we obtain a set of observation pairs of labeled samples = , where is the quality class related to the vector of input parameters . To determine the significance of these results, we use the analysis of variance (ANOVA) statistical method, which identifies those factors that cause differences in the averages in the subjective tests results, and determines the significance of the results. Finally, we introduce a novel method to predict an optimal encoding scheme based on canonical discriminant analysis (CDA) for feature classification.
EURASIP Journal on Advances in Signal Processing, 2005
Transmission of a compressed video signal over a lossy communication network exposes the informat... more Transmission of a compressed video signal over a lossy communication network exposes the information to losses and errors, which leads to significant visible errors in the reconstructed frames at the decoder side. In this paper we present a new hybrid error concealment algorithm for compressed video sequences, based on temporal and spatial concealment methods. We describe spatial and temporal techniques for the recovery of lost blocks. In particular, we develop postprocessing techniques for the reconstruction of missing or damaged macroblocks. A new decision support tree is developed to efficiently choose the best appropriate error concealment method, according to the spatial and temporal characteristics of the sequence. The proposed algorithm is compared to three error concealment methods: spatial, temporal, and a previous hybrid approach using different noise levels. The results are evaluated using four quality measures. We show that our error concealment scheme outperforms all the other three methods for all the tested video sequences.
ABSTRACT One result of the recent advances in different components of imaging systems technology ... more ABSTRACT One result of the recent advances in different components of imaging systems technology is that, these systems have become more resolution-limited and less noise-limited. The most useful tool utilized in characterization of resolution-limited systems is the ...
Applied Optics, 2010
Infrared imagery sequences are used for detecting moving targets in the presence of evolving clou... more Infrared imagery sequences are used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research concentrates on slow-moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. The infrared (IR) imagery sequences that are captured by ground sensors contain an enormous amount of data. Since transmitting this data to a base unit or storing it consumes considerable time and resources, a compression method that maintains the point target detection capabilities is desired. For this purpose, we developed two temporal compression methods that preserve the temporal profile properties of the point target. We evaluated the proposed compression methods using a signal-to-noise-ratio (SNR)-based measure for point target detection and showed that the compression may improve the SNR results compared to the IR sequence prior to compression.
… Engineers in Israel ( …, 2012
ABSTRACT Hyperspectral (HS) image sensors measure the reflectance of each pixel at a large number... more ABSTRACT Hyperspectral (HS) image sensors measure the reflectance of each pixel at a large number of narrow spectral bands, creating a three-dimensional representation of the captured scene. Since the HS image (HSI) consumes a great amount of storage space and transmission time, it would be desirable to reduce the image representation to the extent possible using a compression method, which corresponds to the usage and processing of the image. Many compression methods have been proposed, aiming at different applications and fields. This research focuses on lossy compression of images that contain sub-pixel targets. This target type requires minimum compression loss over the spatial dimension, in order to preserve the target, and the maximum possible spectral compression that would still enable target detection. For this target type, we propose the PCA-DCT (principle component analysis followed by discrete cosine transform) compression method. It combines the PCA ability to extract the background from a small number of components, with the individual spectral compression of each pixel of the residual image, using quantized DCT coefficients. The compression method is kept simple for fast processing and implementation, and considers lossy compression only on the spectral axis. It achieves compression ratio of over 20, while using only spectral compression (before applying spatial compression and bit-stream-encoding). The popular RX (Reed Xiaoli) algorithm and the improved quazi-local RX (RXQLC) are used as target detection methods. The detection performance is evaluated using ROC (receiver operating characteristics) curve generation. The proposed compression method shows improved detection performance, compared to the detection performance of the original image, and of two other compression methods: PCA-ICA and band decimation.
… Engineers in Israel ( …, 2012
ABSTRACT Infrared imagery sequences are used for detecting moving targets in the presence of evol... more ABSTRACT Infrared imagery sequences are used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. Since transmitting infrared (IR) imagery sequences to a base unit or storing them consume considerable time and resources, a compression method which maintains the point target detection capabilities is desired. In our previous work, we introduced two temporal compression methods, which preserve the temporal profile properties of the point target, in the form of the discrete cosine transform (DCT) quantization and the parabola fit. In the present work, we continue the compression task method of the DCT quantization by applying spatial compression over the temporally compressed coefficients, followed by bit encoding. We evaluate the proposed compression methods using an SNR-based measure for point target detection. Furthermore, we introduce an automatic detection algorithm of the target tracks that extracts the target location from the SNR scores image, which is acquired during the evaluation process. We previously determined that it is necessary to establish a minimal noise level in the SNR-based measure, to compensate for smoothing that is induced by the compression. Here, the noising process is modified, in order to allow detection of targets traversing all background types.
SPIE Proceedings, 1999
ABSTRACT One result of the recent advances in different components of imaging systems technology ... more ABSTRACT One result of the recent advances in different components of imaging systems technology is that, these systems have become more resolution-limited and less noise-limited. The most useful tool utilized in characterization of resolution-limited systems is the ...
Applied Optics, 2016
Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of... more Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow-moving point targets that are less than one pixel in size, such as aircraft at long range from a sensor. Since transmitting IR imagery sequences to a base unit or storing them consumes considerable time and resources, a compression method that maintains the point target detection capabilities is highly desirable. In this work, we introduce a new parametric temporal compression that incorporates Gaussian fit and polynomial fit. We then proceed to spatial compression by spatially applying the lowest possible number of bits for representing each parameter over the parameters extracted by temporal compression, which is followed by bit encoding to achieve an end-to-end compression process of the sequence for data storage and transmission. We evaluate the proposed compression method using the variance estimation ratio score (VERS), which is a signal-to-noise ratio (SNR)-based measure for point target detection that scores each pixel and yields an SNR scores image. A high pixel score indicates that a target is suspected to traverse the pixel. From this score image we calculate the movie scores, which are found to be close to those of the original sequences. Furthermore, we present a new algorithm for automatic detection of the target tracks. This algorithm extracts the target location from the SNR scores image, which is acquired during the evaluation process, using Hough transform. This algorithm yields a similar detection probability (PD) and false alarm probability (PFA) of the compressed sequences and the original sequences. The parameters of the new parametric temporal compression successfully differentiate the targets from the background, yielding high PDs (above 83%) with low PFAs (below 0.043%) without the need to calculate pixel scores or to apply automatic detection of the target tracks.
Optical Engineering, 2001
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
2006 International Conference on Information Technology: Research and Education, 2006
... Ron Shmueli(b), Ofer Hadar(a), Revital Huber(a), Masha Maltz(c) Merav Huber(a) ... The percei... more ... Ron Shmueli(b), Ofer Hadar(a), Revital Huber(a), Masha Maltz(c) Merav Huber(a) ... The perceived visual information is affected by the network in a different manner than data or voice services [1]. Measuring and modeling networks capabilities with relation to visual information is ...
2006 International Conference on Information Technology: Research and Education, 2006
ABSTRACT
Signal and Data Processing of Small Targets 2013, 2013
ABSTRACT Infrared (IR) imagery sequences are commonly used for detecting moving targets in the pr... more ABSTRACT Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. The target detection performance is measured via the variance estimation ratio score (VERS), which essentially calculates the pixel scores of the sequences, where a high score indicates a target is suspected to traverse the pixel. VERS uses two parameters - long and short term windows, which were predetermined individually for each movie, depending on the target velocity and on the clouds intensity and amount, as opposed to clear sky (noise), in the background. In this work, we examine the correlation between the sequences' spatial and temporal features and these two windows. In addition, we modify VERS calculation, to enhance target detection and decrease cloud-edge scores and false detection. We conclude this work by evaluating VERS as a detection measure, using its original version and its modified version. The test sequences are both original real IR sequences as well as their relative compressed sequences using our designated temporal DCT quantization method.
Optical Engineering, 2004
We evaluate the degradation in a video sequence that suffers from increasing packet loss ratio (P... more We evaluate the degradation in a video sequence that suffers from increasing packet loss ratio (PLR), by using several kinds of quality measures, namely, mean square error (MSE); (the root MSE, which is weighted by the maximum signal change between pairs of pixelsthe ...
Optical Engineering, 2006
We analyze the connection between viewer-perceived quality and encoding schemes. The encoding sch... more We analyze the connection between viewer-perceived quality and encoding schemes. The encoding schemes depend on transmission bit-rate, MPEG compression depth, frame size and frame rate in a constant bit-rate (CBR) video transmission of a MPEG-2 video sequence. The ...
IEEE Transactions on Broadcasting, 2000
We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP net... more We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP network with a quality of service mechanism. The parameters of the encoding schemes include the transmission bit rate, the compression depth, the frame size and the frame rate. We demonstrate that when jointly considering the impact of the coding bit rate, the packet loss ratio and the video characteristics, we can identify an optimal encoding scheme that maximizes viewer-perceived quality. The video content, the compression and the transmission are represented by a vector which contains parameters. Based on subjective tests, we obtain a set of observation pairs of labeled samples = , where is the quality class related to the vector of input parameters . To determine the significance of these results, we use the analysis of variance (ANOVA) statistical method, which identifies those factors that cause differences in the averages in the subjective tests results, and determines the significance of the results. Finally, we introduce a novel method to predict an optimal encoding scheme based on canonical discriminant analysis (CDA) for feature classification.
EURASIP Journal on Advances in Signal Processing, 2005
Transmission of a compressed video signal over a lossy communication network exposes the informat... more Transmission of a compressed video signal over a lossy communication network exposes the information to losses and errors, which leads to significant visible errors in the reconstructed frames at the decoder side. In this paper we present a new hybrid error concealment algorithm for compressed video sequences, based on temporal and spatial concealment methods. We describe spatial and temporal techniques for the recovery of lost blocks. In particular, we develop postprocessing techniques for the reconstruction of missing or damaged macroblocks. A new decision support tree is developed to efficiently choose the best appropriate error concealment method, according to the spatial and temporal characteristics of the sequence. The proposed algorithm is compared to three error concealment methods: spatial, temporal, and a previous hybrid approach using different noise levels. The results are evaluated using four quality measures. We show that our error concealment scheme outperforms all the other three methods for all the tested video sequences.
ABSTRACT One result of the recent advances in different components of imaging systems technology ... more ABSTRACT One result of the recent advances in different components of imaging systems technology is that, these systems have become more resolution-limited and less noise-limited. The most useful tool utilized in characterization of resolution-limited systems is the ...
Applied Optics, 2010
Infrared imagery sequences are used for detecting moving targets in the presence of evolving clou... more Infrared imagery sequences are used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research concentrates on slow-moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. The infrared (IR) imagery sequences that are captured by ground sensors contain an enormous amount of data. Since transmitting this data to a base unit or storing it consumes considerable time and resources, a compression method that maintains the point target detection capabilities is desired. For this purpose, we developed two temporal compression methods that preserve the temporal profile properties of the point target. We evaluated the proposed compression methods using a signal-to-noise-ratio (SNR)-based measure for point target detection and showed that the compression may improve the SNR results compared to the IR sequence prior to compression.
… Engineers in Israel ( …, 2012
ABSTRACT Hyperspectral (HS) image sensors measure the reflectance of each pixel at a large number... more ABSTRACT Hyperspectral (HS) image sensors measure the reflectance of each pixel at a large number of narrow spectral bands, creating a three-dimensional representation of the captured scene. Since the HS image (HSI) consumes a great amount of storage space and transmission time, it would be desirable to reduce the image representation to the extent possible using a compression method, which corresponds to the usage and processing of the image. Many compression methods have been proposed, aiming at different applications and fields. This research focuses on lossy compression of images that contain sub-pixel targets. This target type requires minimum compression loss over the spatial dimension, in order to preserve the target, and the maximum possible spectral compression that would still enable target detection. For this target type, we propose the PCA-DCT (principle component analysis followed by discrete cosine transform) compression method. It combines the PCA ability to extract the background from a small number of components, with the individual spectral compression of each pixel of the residual image, using quantized DCT coefficients. The compression method is kept simple for fast processing and implementation, and considers lossy compression only on the spectral axis. It achieves compression ratio of over 20, while using only spectral compression (before applying spatial compression and bit-stream-encoding). The popular RX (Reed Xiaoli) algorithm and the improved quazi-local RX (RXQLC) are used as target detection methods. The detection performance is evaluated using ROC (receiver operating characteristics) curve generation. The proposed compression method shows improved detection performance, compared to the detection performance of the original image, and of two other compression methods: PCA-ICA and band decimation.
… Engineers in Israel ( …, 2012
ABSTRACT Infrared imagery sequences are used for detecting moving targets in the presence of evol... more ABSTRACT Infrared imagery sequences are used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research focuses on slow moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. Since transmitting infrared (IR) imagery sequences to a base unit or storing them consume considerable time and resources, a compression method which maintains the point target detection capabilities is desired. In our previous work, we introduced two temporal compression methods, which preserve the temporal profile properties of the point target, in the form of the discrete cosine transform (DCT) quantization and the parabola fit. In the present work, we continue the compression task method of the DCT quantization by applying spatial compression over the temporally compressed coefficients, followed by bit encoding. We evaluate the proposed compression methods using an SNR-based measure for point target detection. Furthermore, we introduce an automatic detection algorithm of the target tracks that extracts the target location from the SNR scores image, which is acquired during the evaluation process. We previously determined that it is necessary to establish a minimal noise level in the SNR-based measure, to compensate for smoothing that is induced by the compression. Here, the noising process is modified, in order to allow detection of targets traversing all background types.