Digital Image based Real-time Sea Fog Removal Technique using GPU

Abstract

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc. 키워드 : 해무, 해무 제거, GPU, 안전항해 Key word : Sea-fog, Sea-fog Removal, GPU, Safe Navigation Received 20 July 2016, Revised 21 July 2016, Accepted 01 August 2016 * Corresponding Author Hyun-Jun Choi(E-mail:hjchoi@mmu.ac.kr, Tel:+82-61-240-7273) Department of Electronic Engineering, Mokpo Maritime University, Mokpo 58628, Korea Open Access http://doi.org/10.6109/jkiice.2016.20.12.2355 print ISSN: 2234-4772 online ISSN: 2288-4165 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/li-censes/ by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright C The Korea Institute of Information and Communication Engineering. Journal of the Korea Institute of Information and Communication Engineering 한국정보통신학회논문지(J. Korea Inst. Inf. Commun. Eng.) Vol. 20, No. 12 : 2355~2362 Dec. 2016