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Separating Reflection Components Based on Chromaticity and Noise Analysis
October 2004 (vol. 26 no. 10)
pp. 1373-1379
ASCII Text
x 
 
Robby T. Tan, Ko Nishino, Katsushi Ikeuchi, "Separating Reflection Components Based on Chromaticity and Noise Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 10, pp. 1373-1379, October, 2004.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2004.90,
author = {Robby T. Tan and Ko Nishino and Katsushi Ikeuchi},
title = {Separating Reflection Components Based on Chromaticity and Noise Analysis},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {26},
number = {10},
issn = {0162-8828},
year = {2004},
pages = {1373-1379},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2004.90},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Separating Reflection Components Based on Chromaticity and Noise Analysis
IS - 10
SN - 0162-8828
SP1373
EP1379
EPD - 1373-1379
A1 - Robby T. Tan,
A1 - Ko Nishino,
A1 - Katsushi Ikeuchi,
PY - 2004
KW - Reflection components separation
KW - specular reflection
KW - diffuse reflection
KW - dichromatic reflection model
KW - noise analysis
KW - chromaticity
KW - specular-to-diffuse mechanism.
VL - 26
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Many algorithms in computer vision assume diffuse only reflections and deem specular reflections to be outliers. However, in the real world, the presence of specular reflections is inevitable since there are many dielectric inhomogeneous objects which have both diffuse and specular reflections. To resolve this problem, we present a method to separate the two reflection components. The method is principally based on the distribution of specular and diffuse points in a two-dimensional maximum chromaticity-intensity space. We found that, by utilizing the space and known illumination color, the problem of reflection component separation can be simplified into the problem of identifying diffuse maximum chromaticity. To be able to identify the diffuse maximum chromaticity correctly, an analysis of the noise is required since most real images suffer from it. Unlike existing methods, the proposed method can separate the reflection components robustly for any kind of surface roughness and light direction.

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Index Terms:
Reflection components separation, specular reflection, diffuse reflection, dichromatic reflection model, noise analysis, chromaticity, specular-to-diffuse mechanism.
Citation:
Robby T. Tan, Ko Nishino, Katsushi Ikeuchi, "Separating Reflection Components Based on Chromaticity and Noise Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 10, pp. 1373-1379, Oct. 2004, doi:10.1109/TPAMI.2004.90
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