A Evaluation on Removing of Rain from Images
R.Sunanda1, J.Beatrice Seventline2
1R. Sunanda, Department of ECE, GITAM University, Visakhapatnam (Andhra Pradesh), India.
2Dr. J. Beatrice Seventline, Department of ECE, GITAM University, Visakhapatnam (Andhra Pradesh), India.
Manuscript received on 18 August 2019 | Revised Manuscript received on 29 August 2019 | Manuscript Published on 06 September 2019 | PP: 942-945 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F11800886S19/19©BEIESP | DOI: 10.35940/ijeat.F1180.0886S19
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper, different techniques for the detection and removal of rain from images have been reviewed. The performance of each technique varies as the rain reduces the visibility of the scene in the image. Detection and removal of rain needs the discrimination of rain from non-rain pixels. Accuracy of methods depends upon this discrimination. Here merits and demerits of existing methods are discussed, which motivates further research. A rain removal technique has wide applications in indoor and outdoor security surveillance systems, tracking and navigation, entertainment industries and consumer electronics.
Keywords: Rain Streaks, Guided Filter, Dictionary Learning, Sparse Coding, Image Decomposition, Neural Network.
Scope of the Article: Image Processing and Pattern Recognition