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Author:

Wang, Suyu (Wang, Suyu.) | Zhang, Zongxiang (Zhang, Zongxiang.) | Wu, Ying (Wu, Ying.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Hyperspectral imagery has been widely used in various fields for its rich amount of feature information. The quality of hyperspectral imagery has been set higher requirements. As a result of the limitation of imaging semiconductor technology, hyperspectral image resolution needs to be improved by a signal processing method. This paper presents a recovery algorithm of spatial and spectral coordinate super-resolution of hyperspectral image based on redundant dictionary. Compared with the traditional image super-resolution restoration algorithm, the super-resolution restoration in the spectral of hyperspectral image was added on the basis of spatial resolution improvement. The original constraint was added in the algorithm and edges of reconstructed image were sharpened with the Maximum a Posterior. The results show this algorithm can effectively improve spatial and spectral resolution of the hyperspectral imagery.

Keyword:

super-resolution restoration Maximum a Posteriori Hyperspectral imagery redundant dictionary

Author Community:

  • [ 1 ] [Wang, Suyu]Beijing Univ Technol, Sch Software Engn, Beijing Engn Res Ctr IOT Software & Syst, Beijing 100124, Peoples R China
  • [ 2 ] [Zhang, Zongxiang]Beijing Univ Technol, Sch Software Engn, Beijing Engn Res Ctr IOT Software & Syst, Beijing 100124, Peoples R China
  • [ 3 ] [Wu, Ying]Beijing Univ Technol, Sch Software Engn, Beijing Engn Res Ctr IOT Software & Syst, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Wang, Suyu]Beijing Univ Technol, Sch Software Engn, Beijing Engn Res Ctr IOT Software & Syst, 100 Ping Leyuan, Beijing 100124, Peoples R China

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Source :

SEVENTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2015)

ISSN: 0277-786X

Year: 2015

Volume: 9817

Language: English

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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