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政大典藏 > College of Informatics > Department of Computer Science > Proceedings > Item 140.119/129021

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/129021

Title:	Image Denoising based on Overlapped and Adaptive Gaussian Smoothing and Convolutional Refinement Networks
Authors:	彭彥璁 Peng, Yan-Tsung Lin, M.-H. Tang, C.-L. Wu, C.-H.
Contributors:	資科系
Date:	2019-09
Issue Date:	2020-03-02 15:23:01 (UTC+8)
Abstract:	We propose to use overlapped and adaptive Gaussian smoothing (OAGS) and convolutional refinement networks (CRN) to recover images corrupted by salt-and-pepper noise. First, the OAGS method identifies noise pixels and recover them. Then, CRN further improve and restore the recovered results with sharper and clearer edges. Experimental results demonstrate the proposed OAGS+CRN method significantly outperforms state-of-the-art denoising methods.
Relation:	2019 IEEE International Symposium on Multimedia (ISM), University of California, Irvine
Data Type:	conference
DOI link:	https://doi.org/10.1109/ISM46123.2019.00032
DOI:	10.1109/ISM46123.2019.00032
Appears in Collections:	[Department of Computer Science ] Proceedings

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