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Research and Application of Compressive Sensing in Image Processing

Author: GuYong
Tutor: TianXiang
School: South China University of Technology
Course: Computational Mathematics
Keywords: Compressive Sensing Sparse The Second Generation Curvelet Sensing Matrix Reconstruction
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 564
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Abstract


The paper mainly researches on the application of Compressive Sensing in image processing, which is not the same as Shannon Sampling theory. Compressive Sensing has been proposed for the result of mathematical researches in recently, including the sparse of signal, non-relative measurement and construction of signal. It is the solution for coding and decoding of image by priority condition.On the basic of understanding and mastering for mature image compressive theory, this paper gives depth on the technology of image compression and other application of technology of image processing. The process of Compressive Sensing has two parts which are coding and decoding. In coding part, image will be projected from high-dimensional signal to low by measuring or sampling, and gotten stream of code by quantization and entropy coding for the value of sampling or measuring. In decoding part, code will be de-quantized and entropy decoded for measurement data, and gotten the optimal solution from under-definite equation. First of all, in this paper, we have the introduce for Compressive Sensing in detail, including their basic theory, framework and some relative algorithm, and then give the features and advantages of Compressive Sensing in theory; secondly, we have researched Compressive Sensing based on the second generation of curvelet transform, and have proposed for the method for color image by the designed Compressive Sensing; thirdly, using the relationship of the series of video, have proposed for the self-adaptive based on Compressive Sensing, and also have improved the huge of data of video and give the prove for the priority of our program; last and not the least, we have give three fields to explore the importance of Compressive Sensing. On the point of view of sparse and measurement, we have researched on the technology of medical image using Compressive Sensing; on the point of view of non-relative, researched on the technology of detection and estimate, which avoids to reconstruction; and on the point of view of reconstruction, have researched on the technology of watermark and so on. In fact, this paper has proposed for algorithm of image and video based on the second generation of curvelet transform, which has changed the limit of traditional method in image compression, reducing time for data processing and also reconstructing accurate image or video by limit measured data. The paper has looked forward to research prospects in image processing not just in image compression, and then give the core of points of further researches.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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