DocumentCode
926438
Title
Separation of diffuse and specular components of surface reflection by use of polarization and statistical analysis of images
Author
Umeyama, Shinji ; Godin, Guy
Author_Institution
Neurosci. Inst., Nat. Inst. of Adv. Ind. Sci. & Technol., Tsukuba, Japan
Volume
26
Issue
5
fYear
2004
fDate
5/1/2004 12:00:00 AM
Firstpage
639
Lastpage
647
Abstract
The image of an opaque object is created by observing the reflection of the light incident on its surface. The dichromatic reflection model describes the surface reflection as the sum of two components, diffuse and specular terms. The specular reflection component is usually strong in its intensity and polarized significantly compared to the diffuse components. On the other hand, the intensity of the diffuse component is weak and it tends to be unpolarized except near occluding contours. Thus, the observation of an object through a rotating polarizer approximately yields images containing constant diffuse component and specular component of different intensity. In this paper, we show that diffuse and specular components of surface reflection can be separated as two independent components when we apply independent component analysis to the images observed through a polarizer of different orientations. We give a separation simulation of artificial data and also give some separation results of real scenes.
Keywords
image processing; independent component analysis; light polarisation; light reflection; dichromatic reflection model; diffuse components separation; image analysis; independent component analysis; light polarization; rotating polarizer; specular components separation; statistical analysis; surface reflection; Computer Society; Dielectrics; Independent component analysis; Layout; Light scattering; Light sources; Mutual information; Optical polarization; Optical reflection; Statistical analysis; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Simulation; Diffusion; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Models, Biological; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Photometry; Principal Component Analysis; Reproducibility of Results; Scattering, Radiation; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2004.1273960
Filename
1273960
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