Image scaling Research Papers - Academia.edu (original) (raw)

This paper addresses the problem of color image quality assessment. The paper presents a novel image/ video quality metrics, Color-SSIM (color-based structural similarity index), based on CIELAB color model. The main drawback of the SSIM algorithm in the spatial domain is that it is highly sensitive to the translation, rotation and scaling of images. This problem can be solved by applying SSIM to the individual channels of a color image in CIELAB color space and by combining the results from the individual channels into a weighted vector mean. Experimental results show that proposed quality metric is highly correlated with the experimental data collected through subjective experiments.

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- Video, Image Quality, Proceedings, Quality assessment

The growing interest in image scaling is mainly due to the availability of digital imaging devices such as, digital cameras, digital camcorders, 3G mobile handsets, high definition monitors etc. Scaling a digital image is a demanding and very important area of research. Image scaling is an important image processing operation applied in diverse areas in computer graphics. Image scaling can be especially useful when one needs to reduce image file size for email and web documents or increase image size for printing, GIS observation, medical diagnostic etc. With the recent advances in imaging technology, digital images have become an important component of media distribution. In addition, a variety of displays can be used for image viewing, ranging fromhigh-resolution computer monitors to TV screens and low-resolution mobile devices.This paper is focused on different image scaling techniqueswith intent that review to be useful to researchers and practitioners interested in image Scaling.

- by Paresh Virparia
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- Computer Science, Artificial Intelligence, Image scaling

Evaluating whole slide images of histological and cytological samples is used in pathology for diagnostics, grading and prognosis. It is often necessary to rescale whole slide images of a very large size. Image resizing is one of the most common applications of interpolation. We collect the advantages and drawbacks of nine interpolation methods, and as a result of our analysis, we try to select one interpolation method as the preferred solution. To compare the performance of interpolation methods, test images were scaled and then rescaled to the original size using the same algorithm. The modified image was compared to the original image in various aspects. The time needed for calculations and results of quantification performance on modified images were also compared. For evaluation purposes, we used four general test images and 12 specialized biological immunohistochemically stained tissue sample images. The purpose of this survey is to determine which method of interpolation is the best to resize whole slide images, so they can be further processed using quantification methods. As a result, the interpolation method has to be selected depending on the task involving whole slide images.

This paper presents a general-purpose, multi-task, and reconfigurable platform for video and image processing. With the increasing requirements of processing power in many of today's video and image processing applications, it is important to go beyond the software implementation to provide a real-time, low cost, high performance, and scalable hardware platform. In this paper, we propose a system by using the powerful parallel processing architecture in the Field Programmable Gate Array (FPGA) to achieve this objective. Based on the proposed system level architecture and design strategies, a prototype system is developed based on the Xilinx Virtex-II FPGA with the integration of embedded processor, memory control and interface technologies. Our system includes different functional modules, such as edge detection, zoom-in and zoom-out functions, which provides the flexibility of using this system as a general video processing platform according to different application requirements. The final system utilizes about 20% of logic resource, 50% of memory on chip, and has total power consumption around 203 mw.

- by Sachi Desai
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- Image Processing, Video Processing, Parallel Processing, Edge Detection

All image warping algorithms to date are imageindependent, namely, relate only to the geometry of the image plane, ignoring the content of the image. We show that taking the image content into account yields elaborate warping schemes which may be used to enhance, sharpen and scale images. Sharpening the image is achieved by "squashing" the pixels in edge areas, and "stretching" the pixels in flat areas. Since image pixels are only moved, not modified, some drawbacks of classical linear filtering methods are avoided. We also lay the mathematical foundation for the use of an image-dependent warping scheme in traditional warping applications, such as distortion minimization.

- by Craig Gotsman
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- Cognitive Science, Mathematics, Computer Science, Grid Computing