caa a22 4500 605540403 CHVBK 20210128100911.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00371-014-1035-1 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1035-1 Compressive environment matting [Elektronische Daten] [Qi Duan, Jianfei Cai, Jianmin Zheng] The existing high-quality environment matting methods usually require the capturing of a few thousand sample images and spend a few hours in data acquisition. In this paper, a novel environment matting algorithm is proposed to capture and extract the environment matte data effectively and efficiently. First, the recently developed compressive sensing theory is incorporated to reformulate the environment matting problem and simplify the data acquisition process. Next, taking into account the special properties of light refraction and reflection effects of transparent objects, two advanced priors, group clustering and Gaussian priors, as well as other basic constraints are introduced during the matte data recovery process to combat with the limited image samples, suppress the effects of the measurement noise resulted from data acquisition, and faithfully recover the sparse environment matte data. Compared with most of the existing environment matting methods, our algorithm significantly simplifies and accelerates the environment matting extraction process while still achieving high-accurate composition results. Springer-Verlag Berlin Heidelberg, 2014 Picture/image generation nationallicence Modeling and recovery of physical attributes nationallicence Duan Qi School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut Cai Jianfei School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut Zheng Jianmin School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1587-1600 0178-2789 31:12<1587 2015 31 371 https://doi.org/10.1007/s00371-014-1035-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1035-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Duan Qi School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut NATIONALLICENCE 700 1- Cai Jianfei School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut NATIONALLICENCE 700 1- Zheng Jianmin School of Computer Engineering, Nanyang Technological University, Singapore, Singapore aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1587-1600 0178-2789 31:12<1587 2015 31 371