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Digital Image Restoration Research Based on Wavelet-domain

Author: DongXiangJun
Tutor: ChangHongSen
School: South China Normal University
Course: Circuits and Systems
Keywords: Wavelet Image Restoration Deconvolution Denoising Paul edge
CLC: TN911.73
Type: Master's thesis
Year: 2005
Downloads: 303
Quote: 3
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Abstract


The image restoration is a very important area of ??research in digital image processing , and the results of their research has been widely applied to various scientific and engineering fields . Is to balance the requirements of image restoration to remove noise while preserving the image edges and details ; while they are often expressed as a contradiction . Wavelet basis with flexible time- frequency scaling capabilities , can be very effective characterization of the image containing the edge and mutations , edge image denoising Paul wavelet analysis to achieve ideal results . Currently, the digital image restoration tools wavelet research is a hot topic in the field of image restoration . The introductory section reviews the progress of the research work in recent years , image restoration , leads to the main work of this paper . Chapter 1 wavelet transform theory . Highlights the wavelet can be widely used in image processing based on - multiresolution analysis and fast wavelet transform . Chapter 2 studies and analysis of a number of classic image restoration algorithms , including frequency domain algorithm , linear algebra algorithms and parameters model algorithm ; specific analysis of the theory of the algorithm , and explains the advantages and disadvantages of the algorithm . Chapter 3 of the study and analysis of the threshold wavelet - based image restoration algorithms , including wavelet domain deconvolution algorithm , iterative regularization of algorithms and parameters of the model algorithm . These algorithms in the recovery of the edge of the image Paul algorithm has a better performance than the classical recovery . Chapter 4 wavelet domain restoration algorithm Paul marginal high complexity computation time and frequency domain restoration algorithm , but Paul the edge of the poor of the complementary nature of the proposed combination of frequency domain and wavelet domain frequency domain regularized inversion and wavelet domain Wiener filtering restoration algorithm . Algorithm analysis and simulation results show that the algorithm is low plus noise degradation or high increase noise and degraded image , visual effects and performance indicators (MSE ISNR) were significantly better than the simple recovery of the frequency domain and simple wavelet domain restoration, image restoration algorithms have good theoretical and practical significance . The paper concludes the paper work , and future research directions .

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