Dark channel prior based blurred image restoration method using total variation and morphology  

作　　者：Yibing Li Qiang Fu Fang Ye Hayaru Shouno 

机构地区：[1]College of Information and Communication Engineering, Harbin Engineering University [2]Department of Information and Communication Engineering, University of Electro-Communications

出　　处：《Journal of Systems Engineering and Electronics》2015年第2期359-366,共8页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61301095);the Chinese University Scientific Fund(HEUCF130807);the Chinese Defense Advanced Research Program of Science and Technology(10J3.1.6)

摘　　要：The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.

关 键 词：image restoration dark channel prior total variation (TV) morphology transform 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]