Spectral Response Based Regularization Parameter Selection for Total Variation Image Restoration

Abstract

This letter introduces a total variation (TV) image restoration method with adaptive Regularization parameter. Our main contributions are two folds: (1) a novel selection scheme that determines the Regularization parameter of TV model in a global way through exploiting the concept of TV spectral response; (2) an efficient algorithm integrating an estimation-and–renewal strategy and the alternating minimization numerical technique to fast calculate the model solution. Experimental results on degraded images indicate the improved performance of our method, both in visual effects and in quantitative evaluations.