Learning Pixel-Distribution Prior with Wider Convolution for Image Denoising

28 Jul 2017 Peng Liu Ruogu Fang

In this work, we explore an innovative strategy for image denoising by using convolutional neural networks (CNN) to learn pixel-distribution from noisy data. By increasing CNN's width with large reception fields and more channels in each layer, CNNs can reveal the ability to learn pixel-distribution, which is a prior existing in many different types of noise... (read more)

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