Fast color balance and multi-path fusion for sandstorm image enhancement

Abstract

Outdoor images captured during sandstorm weather condition frequently yield color cast and poor visibility, which causes some applications to fail in computer vision, such as video surveillance and object recognition systems. In this paper, a fast color balance method followed by an effective fusion model is proposed to enhance the sandstorm-degraded images. Firstly, color channel compensation and piece-wise affine transform balance the aberrant pixels obtained by camera and remove color cast. Then, multi-path fusion comprising of underexposure and contrast-enhanced inputs is used for visibility enhancement, where saturation and Laplacian contrast are measured as weight maps and constructed for Gaussian pyramids. In order to reduce block effects and artifacts of the reconstructed image, we introduce the multi-scale strategy for each path. Experimental results of both synthetic and real-world sandstorm images demonstrate that the proposed color balance method features high computational efficiency and performs much better than comparative methods in terms of image quality. In addition, our fusion-based method also outperforms existing enhancement algorithms of sandstorm image via qualitative and quantitative evaluations.