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Research on Image Restoration Algorithm in Wavelet Domain

Author: HanLi
Tutor: XiaoZhiYun
School: Inner Mongolia University of Technology
Course: Control Theory and Control Engineering
Keywords: Image Restoration Fourier transform Wavelet Transform Regularized Threshold shrinkage Bivariate model
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 229
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Abstract


Due to the intervention of the measurement process , or other physical conditions , as well as noise , we often can only obtain drop the quality of observation images . The purpose is to image restoration the degraded image processing , its recovery into the ideal image no degradation . Image degradation process is often manifested as a low-pass filter , and thus the image restoration is a typical ill-posed problem . Wavelet basis with flexible time-frequency scaling capabilities , can be very effective to characterize the the edge and mutations image , recovery image using wavelet analysis to maintain the edge able to achieve the desired results . Currently, the digital image restoration tools wavelet research is a hot topic in the field of image restoration . Papers in-depth systematic study of a wide range of image restoration method , wavelet domain restoration algorithm Paul marginal and analysis on the basis of their essential characteristics and the advantages and disadvantages , and leads to a combination of Fourier-domain and wavelet domain image restoration method : high computational complexity , simple but Paul marginal difference frequency-domain restoration algorithm , the complementary nature of the two algorithms . Seen alone in the frequency domain or wavelet domain image restoration , restoration effect and computational efficiency can not be a good compromise ; paper proposes recovery algorithm combined with wavelet domain and frequency domain to provide for the recovery of the degraded image new ideas. In this paper, an improved wavelet domain regularized restoration method , frequency domain regularized inversion the contraction threshold wavelet domain image restoration algorithms , simulation results demonstrate the effectiveness of the algorithm . The bivariate (Bivariate) model is applied to image restoration based on morbid Fourier wavelet regularized deconvolution algorithm (ForWaRD) . To utilize ForWaRD algorithm , first of all fuzzy plus noise degraded image in the Fourier domain The Wiener filter REGULARIZED Deconvolution , then denoising in wavelet domain Bivariate probability distribution function as a natural image wavelet coefficients vector prior model , made ??a good recovery .

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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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