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

作者：Li, Yibing; Fu, Qiang; Ye, Fang^*; Shouno, Hayaru

来源：Journal of Systems Engineering and Electronics, 2015, 26(2): 359-366.

DOI：10.1109/JSEE.2015.00042

• image restoration
• dark channel prior
• total variation (TV)
• morphology transform

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 applications. 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 estimated 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.

• 出版日期2015-4
• 单位哈尔滨工程大学