피사계 심도를 고려한 효율적인 이미지 추상화
A DoF-Based Efficient Image Abstraction
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참고문헌
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초록
본 논문에서는 피사계 심도(DoF, Depth of field)가 포함된 사진을 자동으로 추상화해주는 비 사실적 렌더링(NPR, Non-photorealistic rendering) 기술을 제안한다. 우리의 접근 방식은 RGB 채널을 이용하여 DoF 영역을 효율적으로 분류하고, 이를 기반으로 색상의 추상화와 추출된 라인의 품질을 자동으로 조절하는 새로운 필터링 방법이다. 이 DoF 기반 필터링은 기능 향상 및 디자인 관점에서 추상화 성능을 크게 향상시켰다. 우리의 방법은 간단하고 빠르며 구현하기 쉽다. 결과적으로 사진으로부터 추상화나 일러스트레이션을 작성 할 때 원본 사진이 갖고 있는 특징이나 스타일들을 효율적으로 잘 표현한다.
Abstract
In this paper, We present a non-photorealistic rendering technique that automatically delivers a stylized abstraction of a photograph with DoF(Depth of field). Our approach is a new filtering method that efficiently classifies DoF regions using RGB channels and automatically adjusts the color abstraction and extracted line quality based on this classification. This DoF-based filtering significantly improves the abstraction performance in terms of feature enhancement and stylization. Our method is simple, fast, and easy to implement. Experimental results demonstrate the effectiveness of our method in producing stylistic and feature-enhancing illustrations from photographs.
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