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Image Restoration Using Very Deep Convolutional Encoder ...

Image Restoration Using very deep ConvolutionalEncoder-Decoder Networks with Symmetric SkipConnectionsXiao-Jiao Mao , Chunhua Shen?, Yu-Bin Yang State Key Laboratory for Novel Software Technology, Nanjing University, China?School of Computer Science, University of Adelaide, AustraliaAbstractIn this paper, we propose a very deep fully Convolutional encoding-decoding frame-work for Image Restoration such as denoising and super-resolution. The network iscomposed of multiple layers of convolution and deconvolution operators, learningend-to-end mappings from corrupted images to the original ones. The convolu - tional layers act as the feature extractor, which capture the abstraction of imagecontents while eliminating noises/corruptions. Deconvolutional layers are thenused to recover the Image details.

The convolu-tional layers act as the feature extractor which encode the primary components of image contents while eliminating the corruption. The deconvolutional layers then decode the image abstraction to recover the image content details. We propose to add skip connections between corresponding convolutional and deconvolu-tional layers.

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