Open AccessCandidate value‐based boundary filtering for compressed depth images
Author(s) -
Zhao Lijun,
Wang Anhong,
Zeng Bing,
Wu Yingchun
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.3912
Subject(s) - pixel , computer vision , boundary (topology) , filter (signal processing) , artificial intelligence , computer science , depth map , object (grammar) , mathematics , truncation (statistics) , median filter , bilateral filter , image (mathematics) , algorithm , pattern recognition (psychology) , image processing , mathematical analysis , statistics
In three‐dimensional (3D) video, a compressed depth map usually has large distortions along‐boundaries, leading to object deformation and artefacts in synthesised views. A so‐called candidate values based boundary filtering (CVBF) with low computational complexity by filtering only some detected unreliable pixels along the boundaries is proposed. Assuming that the smooth regions consist of reliable pixels, CVBF selects an appropriate candidate value to replace each unreliable pixel based on both the nearest reliable pixels and the mean values of surrounding regions. Experimental results show that synthesised views with CVBF‐filtered depth maps are better than existing joint trilateral filtering, the depth boundary reconstruction filter and the adaptive depth truncation filter.