Iterative Convolutional Neural Network For Noisy Image Super-Resolution
2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)(2017)
摘要
Images captured by camera tend to be noisy and their qualities are often deteriorated in super-resolution. In this paper, we propose an end-to-end convolutional neural network to generate denoised, high-resolution image directly from its noisy, low-resolution counterpart. To preserve textures and eliminate noises simultaneously, the network is organized into an iterative structure for the recovery of high-quality image step by step. Each step of the structure is aimed to learn a better result with reference of its predecessor's output. Experiments show that our method is able to produce more desirable high-resolution images in both objective and subjective evaluations comparing to conventional ones as well as non-iterative network based one.
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关键词
Convolutional Neural Network, iterative structure, super-resolution, denoising, image reconstruction
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