Sub-pixel mapping based on spectral information of irregular scale areas for hyperspectral images
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1.Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application, Ministry of Natural Resources, Zhangzhou Institute of Surveying and Mapping, Zhangzhou 363000, China;2.Anhui Province Key Laboratory of Physical Geographic Environment, Chuzhou University, Chuzhou 239000, China;3.College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;4.School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;5.Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Meteorological Institute of Hebei, Shijiazhuang 050021, China;6.Xi’an Key Laboratory of Territorial Spatial Information, Chang'an University, Xi’an 710064, China

Clc Number:

TP751

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Supported by the Foundation of Anhui Province Key Laboratory of Physical Geographic Environment (2022PGE010); The Fundamental Research Funds for the Central Universities, CHD (300102353508); the Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application, MNR (22101); National Natural Science Foundation of China (61801211); Natural Science Foundation of Jiangsu Province (BK20221478); Hong Kong Scholars Program (XJ2022043); S&T Program of Hebei (21567624H); Open Project Program of Key Laboratory of Meteorology and Ecological Environment of Hebei Province (Z202102YH)

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    Abstract:

    Sub-pixel mapping technology can analyze mixed pixels and realize the transformation from fractional images to fine a land-cover mapping image at the sub-pixel level. However, the spectral information used by the traditional sub-pixel mapping methods is usually constructed in a specified rectangular local window, and the spectral information of all bands is rarely used, affecting the performance of sub-pixel mapping. To solve this issue, sub-pixel mapping based on spectral information of irregular scale areas (SIISA) for hyperspectral images is proposed in this paper. The experimental results on three remote sensing images show the proposed SIISA outperforms the existing sub-pixel mapping methods.

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WANG Peng, CHEN Yong-Kang, ZHANG Gong, WANG Hong-Ying, ZHAO Chun-Lei, HAN Ling. Sub-pixel mapping based on spectral information of irregular scale areas for hyperspectral images[J]. Journal of Infrared and Millimeter Waves,2023,42(4):538~545

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History
  • Received:July 12,2022
  • Revised:June 02,2023
  • Adopted:February 28,2023
  • Online: June 02,2023
  • Published:
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