Adaptive correction procedure for TVL1 image deblurring under impulse noise. (16th June 2016) - Bai, Minru; Zhang, Xiongjun; Shao, Qianqian
Abstract: For the problem of image restoration of observed images corrupted by blur and impulse noise, the widely used TVL1 model may deviate from both the data-acquisition model and the prior model, especially for high noise levels. In order to seek a solution of high recovery quality beyond the reach of the TVL1 model, we propose an adaptive correction procedure for TVL1 image deblurring under impulse noise. Then, a proximal alternating direction method of multipliers (ADMM) is presented to solve the corrected TVL1 model and its convergence is also established under very mild conditions. It is verified by numerical experiments that our proposed approach outperforms the TVL1 model in terms of signal-to-noise ratio (SNR) values and visual quality, especially for high noise levels: it can handle salt-and-pepper noise as high as 90% and random-valued noise as high as 70%. In addition, a comparison with a state-of-the-art method, the two-phase method, demonstrates the superiority of the proposed approach.