Designing Of A Novel Approach For Image Haze Removal Using Color Attenuation Prior (CAP) And Single Scale Retinex (SSR) Hybrid Restoration & Enhancement Techniques

Abstract

Haze is a poor-quality state described by the iridescent appearance of the atmosphere, which reduces visibility. It is caused by high concentrations of atmospheric air pollutants, such as dust, smoke, and other particles that scatter and absorb sunlight. Typically, the images captured in the outside environment have low contrast, color fade, and restricted visibility due to suspended particles of the atmosphere that directly influence the image quality. This can cause difficulty in identifying the objects in the captured hazy images or frames. To address this problem several image dehazing techniques have been developed in the past to address this problem, each of which has its advantages and limitations. Still, effective image restoration and enhancement remains a challenging task. Based on this reasoning, a novel hybrid mechanism is proposed in this research work by combining two existing methods: Color Attenuation Prior (CAP) and Single Scale Retinex (SSR).Regarding post-enhancement, SSR excels, whereas CAP is best served by image restoration and Haze removal. High image noise, poor contrast, a huge haze gradient, Halo Artefacts, lost detail, blurred images, edges that weren't preserved, etc., were all issues the hybrid approach resolved. Parameters including PSNR, SSIM, MSE, the Haze improvement index, and Visibility Metric (VM) have been calculated to evaluate the efficacy of the hybrid approach. The proposed approaches are implemented using the generalized and image processing toolboxes in MATLAB 2016a. Experimental results show that the proposed approach outperforms state–of–the–art haze removal algorithms.