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Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients

Abstract: 

In this paper, we propose a principal color component extraction
method that is simply performed by linear color composition (transformation)
of R, G, B colors, but its composite coefficients are calculated
so as to obtain a noisy-texture-less principal component of
RGB color images. Our method is related to principal component
analysis (PCA) and edge preserving smoothing by total variation
(TV) minimization. The resultant image becomes a principal color
component image with the minimum total variation. We show this
problem can be formulated as TV minimization on a spherical manifold
for a whitened data matrix. Although this spherical constraint is
non-convex, it can be solved by using alternating direction method
of multipliers (ADMM). As its application, we show the results of
text character extraction from ancient wooden tablets, and how our
method extracts faint ink characters while reducing wood grain textures.
Our method is unsupervised but has performance equivalent
to a linear discriminant analysis (LDA) method with user-assisted
information.

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Paper Details

Authors:
Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama
Submitted On:
13 September 2017 - 8:14am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Takuya Sugimoto
Paper Code:
2334
Document Year:
2017
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Document Files

ICIP2017_poster_final.pdf

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ICIP2017_poster_final.pdf

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[1] Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama, "Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1927. Accessed: Sep. 21, 2017.
@article{1927-17,
url = {http://sigport.org/1927},
author = {Takuya Sugimoto; Kazuhiro Fujimori; Keiichiro Shirai; Hidetoshi Miyao; Minoru Maruyama },
publisher = {IEEE SigPort},
title = {Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients},
year = {2017} }
TY - EJOUR
T1 - Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients
AU - Takuya Sugimoto; Kazuhiro Fujimori; Keiichiro Shirai; Hidetoshi Miyao; Minoru Maruyama
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1927
ER -
Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama. (2017). Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients. IEEE SigPort. http://sigport.org/1927
Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama, 2017. Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients. Available at: http://sigport.org/1927.
Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama. (2017). "Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients." Web.
1. Takuya Sugimoto, Kazuhiro Fujimori, Keiichiro Shirai, Hidetoshi Miyao, Minoru Maruyama. Principal Noiseless Color Component Extraction by Linear Color Composition with Optimal Coefficients [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1927