Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale Image Restoration

Image restoration (IR) is a long-standing challenging problem in low-level image processing. It is of utmost importance to learn good image priors for pursuing visually pleasing results. In this paper, we develop a multi-channel and multi-model-based denoising autoencoder network as image prior for...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 29; S. 142 - 156
Hauptverfasser:	Li, Sanqian, Qin, Binjie, Xiao, Jing, Liu, Qiegen, Wang, Yuhao, Liang, Dong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms auxiliary variable technique channel prior denoising autoencoder network Gray-scale Grayscale image restoration Image denoising Image processing Image quality Image restoration Iterative methods Minimization multi-model Noise reduction proximal gradient descent Task analysis Training
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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