Single Image Fog Removal Using WLS Smoothing Filter Combining CLAHE with DWT

Abstract

A clean picture may be restored from a damaged image utilising fog removal methods. The degree of haze or fog that influences the original picture may be determined using the image’s depth information. In this paper, WLS (Weighted Least Square)-based filtering is used to enhance the image. In the post-processing stage, further refining is done, such as local contrast enhancement and increasing fine detail throughout the recovered picture, so that the item in the image can be seen clearly. After that, we have utilised CLAHE (Contrast limited adaptive histogram equalisation) which is a well-known local contrast enhancement approach for improving tiny features in a picture. It might result in over-enhancement and noise production in some sections of a picture. The CLAHE-DWT strategy, which combines CLAHE with DWT (Discrete Wavelet Transform), is employed to overcome these difficulties. As a consequence, more visible image features with sharper objects, which is ideal for human visual perception is obtained. In both subjective and objective evaluations, our suggested strategy outperforms existing methods.