Non-local neighbor embedding image denoising algorithm in sparse domain

Guo-chuan Shi; Liang Xia; Shuang-qing Liu; Guo-ming Xu

doi:10.1117/12.2036660

19 December 2013 Non-local neighbor embedding image denoising algorithm in sparse domain

Guo-chuan Shi, Liang Xia, Shuang-qing Liu, Guo-ming Xu

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 90451C (2013) https://doi.org/10.1117/12.2036660
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

To get better denoising results, the prior knowledge of nature images should be taken into account to regularize the ill-posed inverse problem. In this paper, we propose an image denoising algorithm via non-local similar neighbor embedding in sparse domain. Firstly, a local statistical feature, namely histograms of oriented gradients of image patches is used to perform the clustering, and then the whole training data set is partitioned into a set of subsets which have similar local geometric structures and the centroid of each subset is also obtained. Secondly, we apply the principal component analysis (PCA) to learn the compact sub-dictionary for each cluster. Next, through sparse coding over the sub-dictionary and neighborhood selecting, the image patch to be synthesized can be approximated by its top k neighbors. The extensive experimental results validate the effective of the proposed method both in PSNR and visual perception.

Citation Download Citation

Guo-chuan Shi, Liang Xia, Shuang-qing Liu, and Guo-ming Xu "Non-local neighbor embedding image denoising algorithm in sparse domain", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90451C (19 December 2013); https://doi.org/10.1117/12.2036660

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KEYWORDS

Associative arrays

Principal component analysis

Denoising

Image denoising

Global system for mobile communications

Image processing

Visualization

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