Down-Sampling Dark Channel Prior of Airlight Estimation for Low Complexity Image Dehazing Chip Design

Abstract

Image dehazing is an image processing technique to restore a hazy image back to hazy-free one. Airlight estimation plays an important role in image dehazing algorithm. Dark Channel Prior (DCP) is an efficient algorithm to predict airlight. However, the sorting process of DCP causes tremendous computation requirement, limiting its potential in image dehazing chip design. To overcome this limitation, Down-sampling DCP (DS-DCP) is proposed to provide a low complexity algorithm for airlight estimation. Experiment results demonstrate that the computation saving ratio (CSR) of DS-DCP is as high as 98%, while keeping error as minor as 0.22%.