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http://dx.doi.org/10.3745/JIPS.02.0086

A New Operator Extracting Image Patch Based on EPLL  

Zhang, Jianwei (College of Math and Statistics, Nanjing University of Information Science and Technology)
Jiang, Tao (College of Math and Statistics, Nanjing University of Information Science and Technology)
Zheng, Yuhui (Jiangsu Engineering Centre of Network Monitoring, College of Computer and Software, Nanjing University of Information Science and Technology)
Wang, Jin (School of Computer & Communication Engineering, Changsha University of Science & Technology)
Xie, Jiacen (College of Math and Statistics, Nanjing University of Information Science and Technology)
Publication Information
Journal of Information Processing Systems / v.14, no.3, 2018 , pp. 590-599 More about this Journal
Abstract
Multivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.
Keywords
Expected Patch Log Likelihood; Image Denoising; Patch Priors; Structure Information;
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