Abstract
The images in the haze domains have noise and low contrast in dynamic ranges require some analysis. The purpose of this study is to propose an automatic algorithm that will improve the quality of hazy images. In this approach, a sequence of techniques are employed in different steps in order to achieve the quality. The Wiener filter is utilized for image restoration, contrast spreading by RBG color model, YCbCr color model is used for luminance spreading, and the cast removed by white balance. A comprehensive set of experiments are performed on publicly available haze dataset in order to assess the performance of the proposed approach. It is obvious that the proposed method showed significant performance in enhancing hazy images. Moreover, in comparison, the performance of the proposed method is much better against conventional methods such as multi-scale fusion and histogram equalization. Similarly, complexity-wise the proposed algorithm is better than of the existing works, which consequently best choice for real time dehazing.