A New Genetic Method for Subpixel Mapping Using Hyperspectral Images
- 3 March 2016
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Vol. 9 (9), 4480-4491
- https://doi.org/10.1109/jstars.2015.2496660
Abstract
Subpixel mapping techniques aim to obtain the spatial location and distribution of subpixels by transforming the information coming from a set of input abundance maps into a classification result with higher spatial resolution. However, traditional subpixel mapping algorithms generally ignore the possible errors that are due to abundance estimation inaccuracies by spectral unmixing techniques. In this paper, we propose a new genetic algorithm-based subpixel mapping technique that solves the subpixel mapping problem by correcting the potential errors in the estimated abundance fractions used as input to the subpixel mapping process. The proposed algorithm has been compared with other two genetic subpixel mapping methods, using both synthetic and real hyperspectral images. Our experimental results demonstrate that the proposed approach outperforms traditional subpixel mapping algorithms, thus providing an effective option to improve the accuracy of subpixel mapping for remotely sensed hyperspectral images.Keywords
Funding Information
- China Postdoctoral Science Foundation (2014M560353, 2015T80450)
- National Natural Science Foundation of China (41401398, 41325005, 41201426, 41171352, 41171327)
- Fund of Shanghai Outstanding Academic Leaders Program (12XD1404900)
- Kwang-Hua Foundation of College of Civil Engineering, Tongji University
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