Image Dehazing using AHE with Noise Removal using CLAHE and Postprocessing using Gamma Correction

This paper proposes a modified version of Adaptive Histogram Equalization (AHE) with noise removal using Contrast Limiting Adaptive Histogram Equalization (CLAHE) and Postprocessing using Gamma Correction. The algorithm works on a primary haze dataset containing 55 haze images collected from the neighboring environment. The algorithm constitutes multiple steps including input image partitioning, histogram calculation, calculating normalized equalized histogram, creating each contextual region using the bilinear interpolation, performing Contrast Limiting Adaptive Histogram Equalization, computing the Cumulative Distribution Function, the mapping function, and producing the output image after CLAHE, performing postprocessing, and output image generation. Performance of the proposed approach is measured in multiple quantitative ways, via several performance parameters such as SNR, PSNR, MSE, RMSE, SSIM etc. The resultant table shows that the performance of the proposed algorithm outperforms the existing benchmark algorithms.