Real-time single image dehazing using block-to-pixel interpolation and adaptive dark channel prior

Abstract

The authors propose a novel and efficient method for single image dehazing. To accelerate the transmission estimation process, a block-to-pixel interpolation method is used for fine dark channel computation, in which the block-level dark channel is first computed, and then the fine pixel-level dark channel is obtained by a weighted voting of the block-level dark channel to preserve edges and smooth out texture noise. This technique can be used for a direct transmission map generation without a computationally expensive refinement step. Since the dark channel prior (DCP) is not valid in bright (sky) regions, they propose an adaptive DCP modelled by a Gaussian curve that produces a more natural recovered image of the sky and other bright regions. In addition, a scaling method for transmission map computation is proposed to further accelerate the dehazing method. Through experiments, they show that the proposed adaptive block-to-pixel technique is about 30 times faster and produces improved recovered images than the well-known state-of-the-art DCP approach.