A New Operator Extracting Image Patch Based on EPLL

Jianwei Zhang, Tao Jiang, Yuhui Zheng, Jin Wang and Jiacen Xie
Volume: 14, No: 3, Page: 590 ~ 599, Year: 2018
10.3745/JIPS.02.0086
Keywords: Expected Patch Log Likelihood, Image Denoising, Patch Priors, Structure Information
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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.

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Cite this article
IEEE Style
Jianwei Zhang, Tao Jiang, Yuhui Zheng, Jin Wang, and Jiacen Xie, "A New Operator Extracting Image Patch Based on EPLL," Journal of Information Processing Systems, vol. 14, no. 3, pp. 590~599, 2018. DOI: 10.3745/JIPS.02.0086.

ACM Style
Jianwei Zhang, Tao Jiang, Yuhui Zheng, Jin Wang, and Jiacen Xie, "A New Operator Extracting Image Patch Based on EPLL," Journal of Information Processing Systems, 14, 3, (2018), 590~599. DOI: 10.3745/JIPS.02.0086.