A double total variation regularized model of Retinex theory based on nonlocal differential operators
Yuanyuan Zang, Zhenkuan Pan, Jinming Duan, Guodong Wang, Weibo Wei · 2013
Image characteristics, such as texture, edge, smoothness, can be much better preserved by using nonlocal differential operators based on patch-distances in image processing. In this paper, we apply with nonlocal differential operators to some existing variation models of Retinex, such as the nonlocal variation model of Retinex (NL_VR); the nonlocal TV regularized model (NL_TV_R) and the nonlocal total variation regularized model with constraints (NL_TV_C). And then we improve and establish a double total variation regularized model of Retinex theory (DTV) and the nonlocal double total regularized model (NL_DTV), which could handles better edges in the illumination. Experiments show that our proposed method and Split Bregman algorithm presented in this paper have higher computational efficiency and accuracy.