Weighted map for reflectance and shading separation using a single image

Sung Hsien Hsieh, Chih Wei Fang, Te Hsun Wang, Chien Hung Chu, Jenn Jier James Lien

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


In real world, a scene is composed by many characteristics. Intrinsic images represent these characteristics by two components, reflectance (the albedo of each point) and shading (the illumination of each point). Because reflectance images are invariant under different illumination conditions, they are more appropriate for some vision applications, such as recognition, detection. We develop the system to separate them from a single image. Firstly, a presented method, called Weighted-Map Method, is used to separate reflectance and shading. A weighted map is created by first transforming original color domain into new color domain and then extracting some useful property. Secondly, we build Markov Random Fields and use Belief Propagation to propagate local information in order to help us correct misclassifications from neighbors. According to our experimental results, our system can apply to not only real images but also synthesized images.

Original languageEnglish
Title of host publicationComputer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers
Number of pages11
EditionPART 3
Publication statusPublished - 2010 Dec 29
Event9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, China
Duration: 2009 Sep 232009 Sep 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5996 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th Asian Conference on Computer Vision, ACCV 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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