Learning Non-Negativity Constrained Variation for Image Denoising and Deblurring

Tengda Wei, Linshan Wang, Ping Lin, Jialing Chen, Yangfan Wang, Haiyong Zheng
2017 Numerical Mathematics: Theory, Methods and Applications  
This paper presents a heuristic Learning-based Non-Negativity Constrained Variation (L-NNCV) aiming to search the coefficients of variational model automatically and make the variation adapt different images and problems by supervised-learning strategy. The model includes two terms: a problem-based term that is derived from the prior knowledge, and an image-driven regularization which is learned by some training samples. The model can be solved by classical ε-constraint method. Experimental
more » ... lts show that: the experimental effectiveness of each term in the regularization accords with the corresponding theoretical proof; the proposed method outperforms other PDE-based methods on image denoising and deblurring.
doi:10.4208/nmtma.2017.m1653 fatcat:d2p476fv4zbqbcssx5j6tjttdu