论文标题
小组稀疏编码图像denoising
Group Sparse Coding for Image Denoising
论文作者
论文摘要
组稀疏表示表明在GSR [3]中图像删除和图像对图像中的结果表现出了令人鼓舞的结果，导致成功的主要原因是通过在自然图像上的斑块之间利用稀疏性和非本地自相似性（NSS），并求解一个正则化优化问题。然而，在图像中直接适应GSR [3]，以克服这些问题，为了克服这些问题而产生的产量非常不稳定和不满意的结果，本文提出了一种渐进式图像，以成功调整GSR [3]模型，并且实验显示出优越的性能，而不是一些即将到来的方法。
Group sparse representation has shown promising results in image debulrring and image inpainting in GSR [3] , the main reason that lead to the success is by exploiting Sparsity and Nonlocal self-similarity (NSS) between patches on natural images, and solve a regularized optimization problem. However, directly adapting GSR[3] in image denoising yield very unstable and non-satisfactory results, to overcome these issues, this paper proposes a progressive image denoising algorithm that successfully adapt GSR [3] model and experiments shows the superior performance than some of the state-of-the-art methods.
