Residual Dense Network for Image Restoration

Recently, deep convolutional neural network (CNN) has achieved great success for image restoration (IR) and provided hierarchical features at the same time. However, most deep CNN based IR models do not make full use of the hierarchical features from the original low-quality images; thereby, resulti...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 43; H. 7; S. 2480 - 2495
Hauptverfasser:	Zhang, Yulun, Tian, Yapeng, Kong, Yu, Zhong, Bineng, Fu, Yun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks compression artifact reduction Feature extraction hierarchical features Image coding Image compression image deblurring Image denoising Image quality Image resolution Image restoration image super-resolution Noise reduction Residual dense network Task analysis Training
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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