Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/33334
Title: Image Denoising Via L1 Norm Regularization Over Adaptive Dictionary
Authors: HUANG XINHAI
Keywords: Image denoise, K-SVD, Dictionary updating
Issue Date: 17-Jan-2012
Citation: HUANG XINHAI (2012-01-17). Image Denoising Via L1 Norm Regularization Over Adaptive Dictionary. ScholarBank@NUS Repository.
Abstract: This thesis aims at developing an e cient image denoising method that is adaptive to image contents. The basic idea is to learn a dictionary from the given degraded image over which the image has the optimal sparse approximation. The proposed approach is based on an iterative scheme that alternatively re nes the dictionary and corresponding s- parse approximation of the true image. There are two steps in this approach. One is the sparse coding part which nds the sparse approx- imation of true image via the accelerated proximal gradient algorithm; the other is the dictionary updating part which sequentially updates the elements of the dictionary in a greedy manner. The proposed approach is applied to image de-noising problems. The results from the proposed approach are compared favorably against those from other methods.
URI: http://scholarbank.nus.edu.sg/handle/10635/33334
Appears in Collections:Master's Theses (Open)

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