Physics-based extraction of intrinsic images from a single image

Yun Chung Chung*, Jung Ming Wang, Robert R. Bailey, Sei Wang Chen, Shyang Lih Chang, Shen Cherng

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

A technique for extracting intrinsic images, including the reflectance and illumination images, from a single color image is presented. The technique first convolves the input image with a prescribed set of derivative filters. The pixels of filtered images are then classified into reflectance-related or illumination-related based on a set of chromatic characteristics of pixels calculated from the input image. Chromatic characteristics of pixels are defined by a photometric reflectance model based on the Kubelka-Munk color theory. From the classification results of the filtered images, the intrinsic images of the input image can be computed. Real images have been utilized in our experiments. The results have indicated that the proposed technique can effectively extract the intrinsic images from a single image.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages693-696
Number of pages4
DOIs
Publication statusPublished - 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 2004 Aug 232004 Aug 26

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Conference

ConferenceProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period2004/08/232004/08/26

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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