V-channel Adaptive Defogging with Low Illumination Images Based on Optimized Retinex Model

The defogging effects of different retinex algorithms, including single-scale retinex (SSR), multiscale retinex (MSR) and multiscale retinex with color restoration (MSRCR), are compared in this paper. It was found that some images treated by the above methods were dark. This phenomenon is more obvious when processing foggy images with low light. Contrast limited adaptive histogram equalization (CLAHE) is applied to improve the image brightness and contrast. Further analysis of the V-channel in HSV space shows that when the normalized histogram distribution of the V-channel is concentrated below 0.5 and the image has the component of the highlighted region, the images are dark after processing by the traditional retinex algorithms. Based on this, the V-channel adaptive enhancement method is proposed to improve the overall image brightness. The experiments show that the proposed algorithm works better when combined with both the modified MSR algorithm and CLAHE. The overall brightness of the image is improved, and the information entropy of the image is also increased.