Sparse representation-based image restoration via nonlocal supervised coding

作者：Li, Ao^*; Chen, Deyun; Sun, Guanglu; Lin, Kezheng

来源：Optical Review, 2016, 23(5): 776-783.

DOI：10.1007/s10043-016-0267-x

• Image restoration
• Sparse coding
• Nonlocal technique
• Nonnegative supervised weight
• Iterative shrinkage

Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.

• 出版日期2016-10
• 单位哈尔滨学院