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Author:

Cao Yang (Cao Yang.) | Li Xiaoguang (Li Xiaoguang.) | Zhuo Li (Zhuo Li.) | Shen Lansun (Shen Lansun.)

Indexed by:

CPCI-S

Abstract:

A low-resolution face image is segmented into detailed regions and flat regions. The detailed regions are super resolved using classified predictors according to the local textural structures, while, the flat regions are magnified using bilinear interpolation. Experimental results show that both the visual quality and the computational cost are improved.

Keyword:

super-resolution human face learning-based

Author Community:

  • [ 1 ] [Cao Yang]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 2 ] [Li Xiaoguang]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 3 ] [Zhuo Li]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 4 ] [Shen Lansun]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

Reprint Author's Address:

  • [Cao Yang]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

Email:

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Source :

PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9

Year: 2009

Page: 856-858

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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