Enhanced Image De-Hazing Using Novel Hybrid Filtering and Perceptual Fog Density Improvement

Image de-hazing processes improve visual clarity and image quality, particularly in areas where sight is limited. This study proposes a novel hybrid methodology with the goal of outperforming the limitations of existing de-hazing strategies. We propose a filtering methodology in this study that combines the advantages of Guided Image Filtering (GIF), Weighted Guided Image Filtering (WGIF), and Globally Guided Image Filtering (WGIF) into a single strategy. The proposed solution is a multi-stage framework in which the three de-hazing techniques are utilized consecutively. GIF is first applied to the foggy image. Following that, WGIF is used, followed by GGIF. Finally, we have included a bilateral filter into the hybrid filter to increase the visual quality of the photos even further. Furthermore, the quality of de-hazed photographs is evaluated using a metric known as Perceptual Fog Density (PFD). For evaluating the performance of the proposed methodology, experiments are done over various hazy images of varying haze levels. When comparing the results obtained from the proposed novel strategy to standard de-hazing procedures, it becomes evident that the proposed approach offers notable advantages in terms of both Perceptual Fog Density (PFD) and visual quality.