Abstract:
Rain streaks are known to cause many performance or accuracy reductions in many computer vision systems. The problem of obstructing rain streaks is addressed within the domain of “De-raining”. De-raining is the process of removing rain streaks. It has two main sub-categories which are video de-raining and single image de-raining. Many works on single image de-raining have taken place using both traditional approaches as well as deep learning approaches. This paper does a critical analysis of credible, novel, and best performing single image de-raining systems. Also, the paper addresses an unpaired training gap which exists within the domain with the novel de-raining system ”DERAINIZER”, enabling all future researchers to employ unpaired training data to train their models. It is followed by results, research limitations and possible future works.
