Empirical Review on Video Frame Quality Enhancement Techniques with Improved Background Modeling
Abstract
Digital video has become crucial and ubiquitous in our everyday lives. Though visual frame enhancement algorithms exist in abundance, a universal approach for the applications is scarce. In this paper, an empirical review on the Video Frame Quality Enhancement techniques in Spatial, Transform domain and existing state of the art Hybridization techniques with improved modeling is presented. The challenges and solutions that exist in the background modeling with inconsistent illumination is deliberated. Further the experimentation test beds and performance metrics for illumination inconsistency is put forth. This experiential review can serve as a basis for the major breakthrough of cascaded and clustering approaches in illumination inconsistency reduction.