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Proceedings Paper

Design and implementation of airborne hyperspectral data processing platform compatible with intelligent processing algorithms
Author(s): Kecheng Gong; Yuanxi Peng; Tian Jiang; Hao Hao; Lixiong Zhang; Yongtao Yu
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Paper Abstract

With the continuous expansion of hyperspectral application scenarios, the traditional universal hyperspectral data processing software system is difficult to meet the needs of the industry, and cannot be quickly connected to the intelligent processing algorithm developed by the industry, which has become one of the bottlenecks in the promotion of hyperspectral to practical applications. In order to meet the needs of various industries for professional processing of hyperspectral data, fast access to intelligent processing algorithm, and highly efficient and reliable transplantation of intelligent processing algorithm to airborne platform, this paper designs an airborne hyperspectral data processing platform compatible with intelligent processing algorithms. The software architecture of "Platform + Plug-in" is realized, which provides comprehensive support for hyperspectral image processing and enables users to focus on the development of intelligent processing algorithms, which can be compatible with different intelligent processing algorithms through simple configuration.

Paper Details

Date Published: 31 January 2020
PDF: 9 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272C (31 January 2020); doi: 10.1117/12.2552335
Show Author Affiliations
Kecheng Gong, National Univ. of Defense Technology (China)
Yuanxi Peng, National Univ. of Defense Technology (China)
Tian Jiang, National Univ. of Defense Technology (China)
Hao Hao, National Univ. of Defense Technology (China)
Lixiong Zhang, National Univ. of Defense Technology (China)
Yongtao Yu, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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