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논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 하윤수
- 발행연도
- 2017
- 저작권
- 한국해양대학교 논문은 저작권에 의해 보호받습니다.
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초록· 키워드
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It is important to haze removal in image processing because it makes it difficult to analyze color information and edge information in marine and aeronautical fields, which are sensitive to meteorological conditions. The DCP(Dark Channel Prior), which estimates the haze using the minimum values of R, G, B information, is the most widely used algorithm to remove haze from the current image information. The DCP algorithm is a method for estimating the amount of haze by using the minimum value of R, G, B information on a local area selected stepwise from a given fog image, and estimating the transmission map to remove the haze. At this time, the haze is estimated from the edge of the boundary to the local area, so that the block artifact inevitably occurs. Therefore, the image analysis performance is not high near the edge.
This paper proposes a haze removal method using an improved transmission map to reduce the block artifact occurred during DCP process which is a representative algorithm for haze removal. The proposed method estimates depth information and edge information in a dark channel using entropy, which are stochastic properties, and predicts the part where block artifact occurs. Using the adaptive window according to the entropy value in the predicted part, new transmission map is obtained, which can reduce the block artifact in the edge of the boundary containing the depth information.
In the conclusion, we can obtain improved fog removal image than transmission map the existing DCP algorithm by using the new transmission map.
This paper proposes a haze removal method using an improved transmission map to reduce the block artifact occurred during DCP process which is a representative algorithm for haze removal. The proposed method estimates depth information and edge information in a dark channel using entropy, which are stochastic properties, and predicts the part where block artifact occurs. Using the adaptive window according to the entropy value in the predicted part, new transmission map is obtained, which can reduce the block artifact in the edge of the boundary containing the depth information.
In the conclusion, we can obtain improved fog removal image than transmission map the existing DCP algorithm by using the new transmission map.
목차
Abstract1. 서론 11.1 연구 배경 11.2 논문의 구성 32. DCP를 기반으로 한 안개제거 42.1 안개 모델링 42.2 DCP 기반의 단일영상 안개 제거 방법 62.3 기존 DCP 안개제거 알고리즘의 문제점 123. 제안하는 안개제거 방법 163.1 엔트로피를 이용한 심도가 반영된 경계선 정보 추출 183.2 적응적인 윈도우를 적용한 전달량 추정에 의한 안개제거 234. 실험 및 고찰 295. 결론 37참고 문헌
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