A Review on Efficient Method of Single Image Dehazing Centered on Multi-Scale Fusion

The visibility of the outdoor images is degraded on account of bad atmosphere conditions. That is principally because of the environment particles such as haze and fog that spread and absorb the light. Haze is an atmospheric singularity that significantly degrades the visibility of outdoor scenes. This paper presents a new single image strategy for the improvement of the visibility of degraded images that are changed. Image fusion is an activity which combines the data from two or more resource images from the same landscape to create one solitary image including more exact information of the scene than the resource images. To preserve the regions with good visibility, their important features get filtered by computing three measures (weight maps): luminance, chromaticity, and saliency. The derived images are weighted by specific weight map followed by Laplacian and Gaussian pyramid representations to reduce artifacts occurred due to weight maps. Subsequently the resulting picture is going to be improved from your past and more obvious. Several studies and research has been completed in the disciplines such as Computer Vision, Parallel and distributed processing, Automatic object detection, Image processing, Robotics and Remote sensing. This paper show effectiveness and the power of a fusion-based strategy of dehazing centered on single degraded image. The method performs a per-pixel manipulation, which is straightforward to implement and then apply the directed filter to improve the image quality. Our effective method demonstrates to yield comparative and even better results than the more complex state-of-the-art techniques but has the advantage to be appropriate for real-time applications.