Haze removal based on refined transmission map for aerial image matching

Abstract

A novel strategy is proposed to address block artifacts in a conventional dark channel prior (DCP). The DCP was used to estimate the transmission map based on patch-based processing, which also results in image blurring. To enhance a degraded image, the proposed single-image dehazing technique restores a blurred image with a refined DCP based on a hidden Markov random field. Therefore, the proposed algorithm estimates a refined transmission map that can reduce the block artifacts and improve the image clarity without explicit guided filters. Experiments were per-formed on the remote-sensing images. The results confirm that the proposed algorithm is superior to the conventional approaches to image haze removal. Moreover, the proposed algorithm is suita-ble for image matching based on local feature extraction.