ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술대회 Closed-Form Solution of Simultaneous Denoising and Hole Filling of Depth Image
Cited 1 time in scopus Download 6 time Share share facebook twitter linkedin kakaostory
저자
김용선
발행일
201810
출처
International Conference on Image Processing (ICIP) 2018, pp.968-972
DOI
https://dx.doi.org/10.1109/ICIP.2018.8451850
협약과제
18HS6500, 실내외 임의공간 실시간 영상 합성을 위한 핵심 원천기술 및 개발툴킷 개발, 구본기
초록
This paper presents a novel Time-of-Flight (ToF) depth recovery algorithm minimizing a new quadratic energy function utilizing depth and infrared data. The proposed energy function consists of a filtering term and a reconstruction term to remove noise and fill holes simultaneously in a depth image. In the filtering term, a new multilateral weight is introduced by fully using available spatial, depth, and infrared information. In the reconstruction term, a Poisson equation for reconstructing a depth image from its gradients is used whereas the depth gradients inside hole regions are interpolated with the proposed infrared-guided moving least squares. The recovered depth data can be obtained by solving a sparse linear system derived from minimizing the proposed energy function. Experimental results demonstrate that the proposed algorithm provides good depth recovery performance without introducing texture copy or blur artifacts compared to the existing methods.
KSP 제안 키워드
Depth Data, Depth image, Hole filling, Infrared data, Least Squares(LS), Moving least squares, Poisson Equation, Recovery algorithm, Recovery performance, Sparse linear system, closed-form solution