Learning Hybrid Sparsity Prior for Image Restoration: Where Deep Learning Meets Sparse Coding

18 Jul 2018 Fangfang Wu Weisheng Dong Guangming Shi Xin Li

State-of-the-art approaches toward image restoration can be classified into model-based and learning-based. The former - best represented by sparse coding techniques - strive to exploit intrinsic prior knowledge about the unknown high-resolution images; while the latter - popularized by recently developed deep learning techniques - leverage external image prior from some training dataset... (read more)

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