Color face image super-resolution reconstruction based on learning

Tao Li; Xiao Hua Wang; Gui Qin Song; Jun Ke Li; Xue Mei Yan

Color face image super-resolution reconstruction based on learning

Tao Li^*, Xiao Hua Wang, Gui Qin Song, Jun Ke Li, Xue Mei Yan

^*Corresponding author for this work

School of Integrated Circuits and Electronics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Proposes a super-resolution algorithm on color face image based on quaternion, combining with the ideas of principal component analysis(PCA) and interpolation. By using singular value decomposition to de-noise the color image, improves the quality of the result, and improves the algorithms when the result is not so faithful to the original face image. Quaternion is used to deal with the three components of R, G, B at the same time to increase the efficiency of the operation and used fully the correction of the three components.

Original language	English
Pages (from-to)	193-196
Number of pages	4
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	30
Issue number	2
Publication status	Published - Feb 2010

Keywords

Color image
Interpolation
Principal component analysis(PCA)
Quaternion
Super-resolution reconstruction

Cite this

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title = "Color face image super-resolution reconstruction based on learning",

abstract = "Proposes a super-resolution algorithm on color face image based on quaternion, combining with the ideas of principal component analysis(PCA) and interpolation. By using singular value decomposition to de-noise the color image, improves the quality of the result, and improves the algorithms when the result is not so faithful to the original face image. Quaternion is used to deal with the three components of R, G, B at the same time to increase the efficiency of the operation and used fully the correction of the three components.",

keywords = "Color image, Interpolation, Principal component analysis(PCA), Quaternion, Super-resolution reconstruction",

author = "Tao Li and Wang, {Xiao Hua} and Song, {Gui Qin} and Li, {Jun Ke} and Yan, {Xue Mei}",

year = "2010",

month = feb,

language = "English",

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journal = "Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology",

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TY - JOUR

T1 - Color face image super-resolution reconstruction based on learning

AU - Li, Tao

AU - Wang, Xiao Hua

AU - Song, Gui Qin

AU - Li, Jun Ke

AU - Yan, Xue Mei

PY - 2010/2

Y1 - 2010/2

N2 - Proposes a super-resolution algorithm on color face image based on quaternion, combining with the ideas of principal component analysis(PCA) and interpolation. By using singular value decomposition to de-noise the color image, improves the quality of the result, and improves the algorithms when the result is not so faithful to the original face image. Quaternion is used to deal with the three components of R, G, B at the same time to increase the efficiency of the operation and used fully the correction of the three components.

AB - Proposes a super-resolution algorithm on color face image based on quaternion, combining with the ideas of principal component analysis(PCA) and interpolation. By using singular value decomposition to de-noise the color image, improves the quality of the result, and improves the algorithms when the result is not so faithful to the original face image. Quaternion is used to deal with the three components of R, G, B at the same time to increase the efficiency of the operation and used fully the correction of the three components.

KW - Color image

KW - Interpolation

KW - Principal component analysis(PCA)

KW - Quaternion

KW - Super-resolution reconstruction

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M3 - Article

AN - SCOPUS:77951990566

SN - 1001-0645

VL - 30

SP - 193

EP - 196

JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

IS - 2

ER -

Color face image super-resolution reconstruction based on learning

Abstract

Keywords

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