A New Operator Extracting Image Patch Based on EPLL
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초록
Multivariate finite mixture model is becoming more and more popular in image processing. Performingimage denoising from image patches to the whole image has been widely studied and applied. However, thereremains a problem that the structure information is always ignored when transforming the patch into thevector form. In this paper, we study the operator which extracts patches from image and then transformsthem to the vector form. Then, we find that some pixels which should be continuous in the image patches arediscontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose anew operator which may keep more information when extracting image patches. We compare the newoperator 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.
Abstract
Multivariate finite mixture model is becoming more and more popular in image processing. Performingimage denoising from image patches to the whole image has been widely studied and applied. However, thereremains a problem that the structure information is always ignored when transforming the patch into thevector form. In this paper, we study the operator which extracts patches from image and then transformsthem to the vector form. Then, we find that some pixels which should be continuous in the image patches arediscontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose anew operator which may keep more information when extracting image patches. We compare the newoperator 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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