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A Study on Application of Image Restoration Based on Compressive Sensing and Sparse Decomposition

Author: XueMing
Tutor: ZhaoYiGong
School: Xi'an University of Electronic Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Image Restoration Compressed sensing Image post-processing Maximum a posteriori estimation Subband extrapolation
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 720
Quote: 7
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Abstract


Involvement of physical principles or technical constraints as well as the noise , the image formation, the process of transmission and recording , and its quality produced different degrees of decline it is necessary to use an image restoration techniques , to restore the original image is not distorted by the degradation observations information. Compressed sensing theory in 2006 , breaking the traditional bottleneck of the Nyquist sampling theorem , the high-resolution signal directly obtain it possible , and has been in the field of image restoration application , their research has important theoretical and practical significance . In addition, the use of classical wavelet image compression technology in low bit-rate compression , decompression image artificial effect , severe degradation , using post-processing techniques to restore and improve the image quality has a great practical significance and application value . This paper focuses on the main line of the still image restoration , compressed sensing theory blurs with noisy image restoration problems and image post-processing of low bit-rate compression based on wavelet transform research and exploration . For the former , proposed a recovery algorithm based on compressed sensing theory in the wavelet domain image Bayes . Compared to the compressed sensing theory has been applied to image restoration algorithms , this algorithm has the advantages of low computational complexity , the structure is simple and easy to implement , the experimental results show that the algorithm is able to improve the main impact of decline in the quality of the different degradation function and noise model image objective quality , compared with the general image restoration algorithm , observing the amount of data that need similar effect , less storage space and computation ; proposed for the latter , based on the wavelet subband extrapolation fusion and Contourlet transform single the loop after the image processing algorithms, the experimental results demonstrate that the algorithm can be appropriately compensated by the wavelet transform coefficients of different scale the relationship between the outer sub-band generated in the compression process of energy and loss of information , effectively improving the low bit rate of the compressed image subjective and objective quality , the degree of improvement is better than other classical algorithm .

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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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