Visibility Improvement In Dehazing By Fusion Of CNN With Gated Recurrent Network - Rasmita lenka, Asimananda Khandual, Mihir narayan Mohanty (International Journal of Advanced Science and Technology, 2020)
Various restoration model depending on the prior knowledge had consider an arduous vision task. Wepresent in this paper an effective algorithm for restoring a recognizable picture from a hazy image.Instead of using conventional methods i.e.; image priors as the restoration process, in form of colorattenuation, dark channels, or color line contrast, we use a point-to-point gated background aggregationstructure to reestablish the final image free from haze.. A hybrid dehazing algorithm of CNN frameworkwith features learning recurrent modeling is applied. The transmission map or its depth of scene,structural attributes is obtained in form of ranking layer is applied with the CNN network model so thathazy images can be captured at same instant. Post processing is carried out by Fast guided filter. Hencethis hybrid model basically gives a inter connection idea between coarse layer and fine layer byextensive results obtained on experimental , simulated and real-world images prove that the proposedalgorithm operates against state-of-the-art algorithms in a beneficial way