An Effective Technique for Single Image Haze Removal using MSMO

Due to scattering of light in an atmosphere, hazy images along with noise, color distortions, block artifacts and low intensity are obtained during the image capturing process. The paper proposes a new approach to deal with the problems as mentioned to achieve a better dehazed image. The methodology involves the Dark Channel Prior (DCP) algorithm followed by multi-scale switching morphological operator (MSMO) and contrast limited adaptive histogram equalization (CLAHE). The two inputs are derived by applying MSMO and CLAHE techniques on DCP algorithm based output image and then final dehazed image is obtained through linear fusion. Extensive experiments have been done on various images collected from BeDDE dataset. Results achieved by the proposed approach demonstrate that the quality of dehazed images have significant improvements in terms of better color preservation, reduced noise and blocking artifacts.