2018/04/09 by Yuki Fujimura, Masaaki Iiyama, Fujimura, Yuki +5
Computer Science · #Advanced Vision and Imaging #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Enhancement Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1804.02836
9 pages, accepted to CVPR 2018
openalex publication_date 2018/04/09 · arxiv created 2018/04/10 · arxiv updated 2018/04/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Images captured in participating media such as murky water, fog, or smoke are degraded by scattered light. Thus, the use of traditional three-dimensional (3D) reconstruction techniques in such environments is difficult. In this paper, we propose a photometric stereo method for participating media. The proposed method differs from previous studies with respect to modeling shape-dependent forward scatter. In the proposed model, forward scatter is described as an analytical form using lookup tables and is represented by spatially-variant kernels. We also propose an approximation of a large-scale dense matrix as a sparse matrix, which enables the removal of forward scatter. Experiments with real and synthesized data demonstrate that the proposed method improves 3D reconstruction in participating media.