An image defogging method using adaptive bi-channel priors

Abstract

Image is the important source of information for modern war. And making effective use of the information from the image would take full advantage of the reconnaissance capability. When images captured under fog, they are vulnerable to suspended particles in the atmosphere of the light scattering, absorption and other effects, and images suffer from quality degradation problems which lead to many difficulties for battlefield reconnaissance and recognition. Combining the dark and bright channel priors (bi-channel priors), the super-pixels are used as local regions, thus local transmission and atmospheric light values are estimated more reliably and efficiently. Furthermore, adaptive bi-channel priors are developed to rectify any incorrect estimation on transmission and atmospheric light values for both white and black pixels those fail to satisfy the assumptions of the bi-channel priors. Experimental results demonstrate that the white and black pixels on the restored UAV image are with excellent fidelity and the proposed method performs better for restoring images in terms of both quantitation and quality, and leads to great improvements in real-time defogging.