DOI QR코드

DOI QR Code

Acceleration for Removing Sea-fog using Graphic Processors and Parallel Processing

그래픽 프로세서를 이용한 병렬연산 기반 해무 제거 고속화

  • Kim, Young-doo (Department of Marine Electronic, Communication and Computer Engineering, Mokpo Maritime University) ;
  • Kwak, Jae-min (Department of Marine Electronic, Communication and Computer Engineering, Mokpo Maritime University) ;
  • Seo, Young-ho (Ingenium College of Liberal Arts, Kwangwoon University) ;
  • Choi, Hyun-jun (Department of Marine Electronic, Communication and Computer Engineering, Mokpo Maritime University)
  • 김영두 (목포해양대학교 해양전자.통신.컴퓨터공학과) ;
  • 곽재민 (목포해양대학교 해양전자.통신.컴퓨터공학과) ;
  • 서영호 (광운대학교 교양학부) ;
  • 최현준 (목포해양대학교 해양전자.통신.컴퓨터공학과)
  • Received : 2017.08.08
  • Accepted : 2017.09.25
  • Published : 2017.10.31

Abstract

In this paper, we propose a technique for high speed removal of sea-fog using a graphic processor. This technique uses a host processor(CPU) and several graphics processors(GPU) capable of parallel processing to remove sea-fog from the input image. In the process of removing sea-fog, the dark channel extraction, the maximum brightness channel extraction, and the calculation of the transmission are performed by the host processor, and the process of refining the transmission by applying the bidirectional filter is performed in parallel through the graphic processor. To verify the proposed parallel processing method, three NVIDIA GTX 1070 GPUs were used to construct the verification environment. As a result, it takes about 140ms when implemented with one graphics processor, and 26ms when implemented using OpenMP and multiple GPGPUs. The proposed a parallel processing algorithm based on the graphics processor unit can be used for safe navigation, port control and monitoring system.

본 논문에서는 그래픽 프로세서를 이용하여 고속으로 해무를 제거하는 기술을 제안한다. 이 기술은 호스트 프로세서(CPU)와 병렬처리가 가능한 여러 개의 그래픽 프로세서를 이용하여 입력영상에서 해무를 제거하는 것이다. 해무를 제거하는 과정 중에서 다크 채널 추출, 최대 밝기 채널 추출, 전달량 계산은 호스트 프로세서에서 수행하고, 양방향 필터를 적용하여 전달량을 정제하는 과정을 그래픽 프로세서를 기반으로 병렬처리하여 연산속도를 높였다. 제안한 병렬처리 기법의 검증을 위해 NVIDIA사의 GTX 1070 GPU를 3개를 사용하여 검증환경을 구성하였다. 구현결과 하나의 그래픽 프로세서로 구현하였을 때는 평균 140ms가 소요되고, OpenMP와 다중 GPGPU를 이용하여 구현하였을 때 26ms 소요되었다. 본 논문에서 제안하는 그래픽 프로세서 기반의 병렬연산 해무제거 기술은 선박의 안전항해, 항만 관제 분야에 사용될 수 있을 것이다.

Keywords

References

  1. National Metrics Framework [Internet]. Available: http://www.index.go.kr.
  2. W. S. Choi, "Image based real time sea fog removal technology for safe navigation of coast sailing," M.S dissertation, Mokpo Maritime University, Mokpo, KR, 2016.
  3. S. G. Narasimhan, and S. K. Nayar, "Contrast restoration of weather degraded images," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 9, no. 6, pp. 713-724, June 2003.
  4. S. H. Kim and G. Y. Hong, "Performance Improvement of Aerial Images Taken by UAV Using Daubechies Stationary Wavelet," Journal of Advanced Navigation Technology, Vol. 20, no. 6, pp. 539-543, Dec. 2016. https://doi.org/10.12673/jant.2016.20.6.539
  5. C. Tomasi, R. Manduchi, "Bilateral filtering for gray and color images," in Proceeding of the Sixth International Conference on Computer Vision , India: IN pp. 839-846, Jan. 1998.
  6. W. S. Choi, Y. H. Lee, Y. H. Seo, and H. J. Choi, "Digital image based real-time sea fog removal technique using GPU," Journal of the Korea Institute of Information and Communication Engineering, Vol. 20, no. 12, pp. 2355-2362, Dec. 2016. https://doi.org/10.6109/jkiice.2016.20.12.2355
  7. Y. H. Lee, E. S. Kim, Y. H. Seo, G. C. Kim, and H. J. Choi, "Accelerated Dehazing Technique using GPGPU," in Proceedings of the Korean Society of Marine Environment & Safety Conference, Mokpo: KR, p. 263, 2017.
  8. E. S. Kim, Y. H. Lee, Y. H. Seo, and H. J. Choi, "Sea-fog Dehazing technique base on GPU for CCTV monitoring and controlling system," in Proceedings of the Korea Contents Association Conference, Daejeon: KR, pp. 459-460, 2017.