Image restoration approach based on structure dictionary learning

In this paper, we propose a new structure dictionary learning method, and perform image restoration based on this approach. First, we define the structure dictionary for the nature image. Second, an iterative algorithm is proposed with the decouple of deblurring and denoising steps in the restoration process, which effectively integrates the Fourier regularization and structure dictionary learning technique into the deconvolution framework. Specifically, we propose an iterative algorithm. In the deblurring step, we involve a regularized inversion of the blur in Fourier domain. Then we remove the remained noise using the structure dictionary learning method in the denoising step. Experiment results show that this approach outperforms 6 state-of-the-art image deconvolution methods in terms of improvement signal to noise rate(ISNR) and visual quality, and the ISNR can be improved by more than 0.5 dB. © 2017, China Science Publishing & Media LTD. All right reserved.