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Relighting abstracted image via salient edge‐guided luminance field optimization
Author(s) -
Liu Chunxiao,
Li Hong,
Peng Qunsheng,
Wang Xun,
Wu Enhua
Publication year - 2013
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1516
Subject(s) - salient , computer science , luminance , computer vision , rendering (computer graphics) , abstraction , artificial intelligence , light field , enhanced data rates for gsm evolution , image (mathematics) , field (mathematics) , computer graphics (images) , mathematics , philosophy , pure mathematics , epistemology
Because existing image abstraction systems can hardly incorporate with the changing light, we present an integrated image abstraction and relighting rendering system, which is based on a salient edge‐guided luminance field optimization approach. For an input image, we first adopt a sparsity prior‐based illumination decomposition method to remove its original illumination and have an intrinsic image. Meanwhile, we iteratively extract the salient edge inside by employing a message‐passing strategy. Then, we simplify this image with a proposed salient edge‐guided image abstraction optimization algorithm in the luminance field. Finally, we put forward a salient edge‐guided image relighting optimization method to simulate the effect of dynamic lighting along different directions. Experiment results show that our system can artistically adjust the illumination of the abstracted image and makes it more vivid. Copyright © 2013 John Wiley & Sons, Ltd.