Images which are captured in outdoor scenes often degrade in quality due to atmospheric conditions induced by suspending particles like mist, haze, fog, etc. which scatter and absorb light before it reaches to the camera. The weather-degraded images directly affect the efficiency of computerized surveillance and monitoring system. In this paper, we propose an efficient haze removal technique which integrates dark channel prior with an ant colony optimization algorithm. Firstly, we use the dark channel prior method to compute dark channel in the hazy image and secondly, ant colony optimization algorithm is applied to make restoration factor for hazy images, adaptive between 0 to 1. The restoration factor in all the previous work is fixed value i.e. 0.1. Experimental-results show that proposed algorithm is effective, robust and is yielding high-contrast images.
목차
Abstract 1. Introduction 2. Mathematical Model of Hazy Image 3. Proposed Method 3.1 Dark Channel Prior 3.2 Transmission Estimation 3.3 Estimating Atmospheric Light Value Based On Variogram 3.4 Recovering the Scene Radiance by Using ACO 4. Experimental Results 5. Qualitative Evaluation 6. Conclusion References
키워드
DehazeDefogSingle imageDark channel prior and ant colony optimization
보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Software Engineering and Its Applications
간기
월간
pISSN
1738-9984
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.9 No.8