Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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Hardware Design of Patch-based Airlight Estimation Algorithm

패치 기반 대기강도 추정 알고리즘의 하드웨어 설계

  • Ngo, Dat (Dept. of Electronics Engineering, Dong-A University) ;
  • Lee, Seungmin (Dept. of Electronics Engineering, Dong-A University) ;
  • Kang, Bongsoon (Dept. of Electronics Engineering, Dong-A University)
  • Received : 2020.06.01
  • Accepted : 2020.06.19
  • Published : 2020.06.30
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Abstract

Dehaze is essential for autonomous driving and intelligent CCTV to operate normally even in foggy weather. The method of airlight estimation is particularly important in dehaze technology. In this paper, we propose a patch-based airlight estimation algorithm and hardware structure that can reduce the amount of unnecessary computation and effectively estimate the airlight in various input images. Proposed algorithm is compared with the popular quad-tree method, and the hardware design is implemented by using XILINX's xc7z045-ffg900 target board as a structure that can satisfy to international standard 4K video in real time.

안개가 낀 악조건의 날씨에서도 자율주행 및 지능형 CCTV가 정상적으로 동작하기 위해 안개 제거 기술이 필수적이다. 안개 제거 기술에서도 특히 대기강도 추정 방법이 중요하다. 본 논문에서는 불필요한 연산량을 줄이고 여러 가지 입력 영상에서도 효과적으로 대기강도를 추정할 수 있는 패치 기반 대기강도 추정 알고리즘과 하드웨어 구조를 제안한다. 알고리즘은 대중적으로 널리 사용되는 쿼드트리 방식과 비교했으며, 하드웨어 설계는 국제 표준 4K 영상에 실시간 대응할 수 있는 구조로써 XILINX사의 xc7z045-ffg900 목표 보드를 사용하여 FPGA 검증을 했다.

Keywords

References

  1. Y. K. Wang and C. T. Fan, "Single Image Defogging by Multiscale Depth Fusion," IEEE Trans. Image Process., vol.23, no.11, pp.4826-4837, 2014. DOI: 10.1109/TIP.2014.2358076
  2. D. Ngo, G. D. Lee, and B. S. Kang, "Improved color attenuation prior for single-image haze removal," Appl. Sci., vol.9, no.19, 4011, 2019. DOI: 10.3390/app9194011
  3. Q. Zhu, J. Mai, and L. Shao, "A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior," IEEE Trans. Image Process., vol.24, no.11, pp.3522-3533, 2015. DOI: 10.1109/TIP.2015.2446191
  4. B. Cai, X. Xu, K. Jia, C. Qing, D. Tao, "Dehaze-Net: An End-to-End System for Single Image Haze Removal," IEEE Trans. Image Process., vol.25, no.11, pp.5187-5198, 2016. https://doi.org/10.1109/TIP.2016.2598681
  5. K. He, J. Sun, and X. Tang, "Single Image Haze Removal Using Dark Channel Prior," IEEE Trans. Pattern Anal. Mach. Intell., vol.33, no.12, pp.2341-2353, 2011. DOI: 10.1109/TPAMI.2010.168
  6. J. H. Kim, J. Y. Sim, and C. S. Kim, "Single image dehazing based on contrast enhancement," in Proc. of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1273-1276, 2011. DOI: 10.1109/ICASSP.2011.5946643
  7. K. Ma, W. Liu, and Z. Wang, "Perceptual evaluation of single image dehazing algorithms," in Proc. of the 2015 IEEE International Conference on Image Processing (ICIP), pp.3600-3604, 2015. DOI: 10.1109/ICIP.2015.7351475