FPGA Implementation of Video Dehazing using Dark Channel Priori Algorithm
P. Anil Kumar1, T. Chandra Sekhar Rao2, S.V. Padmajarani3, D. Chiranjeevi4
1Dr. P. Anil Kumar, Associate Professor, CVR College of Engineering, Hyderabad.
2Dr. T. Chandra Sekhar Rao, Professor, Sri Venkateswara Engineering College, Tirupati.
3Dr. S.V. Padmajarani, Principal, Sree Venkateswara College of Engineering, Nellore.
4D. Chiranjeevi, IAENG Member, Bengaluru.

Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1875-1878 | Volume-8 Issue-5, January 2020. | Retrieval Number: D8801118419/2020©BEIESP | DOI: 10.35940/ijrte.D8801.018520

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© 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: The images captured by the camera are dependent on the illumination and reflectance components. The quality of images is degraded by the atmospheric parameters such as poor illumination intensity, rain, haze and fog. The images affected by fog and haze generally lose edge and color information. The image restoration techniques such as dehazing help in retrieving the edge information, but at the cost of color information. The image enhancement such as image dehazing using a dark channel priori algorithm is performed on the image to improve the information content in the image. In this paper, we propose a method of FPGA implementation of video dehazing using a dark channel priori algorithm. The proposed architecture is implemented using VHDL in Cyclone III FPGA with an operating frequency of 108 Hz. The results of the dark channel priori method are verified with the MATLAB simulation results.
Keywords: Dark Channel Priori Algorithm, Dehazing, FPGA, Hardware Implementation, Image Enhancement, Image Restoration.
Scope of the Article:  Algorithms and Complexity.