This paper aims to provide a framework of the supervised hyperspectral classification, to study the traditional flowchart of hyperspectral image (HIS) analysis and processing. HSI technology has been proposed for many years, and the applications of this technology were promoted by technical advancements.
First, the properties and current situation of hyperspectral technology are summarized. Then, this paper introduces a series of common classification approaches. In addition, a comparison of different classification approaches on real hyperspectral data is conducted. Finally, this survey presents a discussion on the classification results and points out the classification development tendency.
The core of this survey is to review of the state of the art of the classification for hyperspectral images, to study the performance and efficiency of certain implementation measures and to point out the challenges still exist.
The study categorized the supervised classification for hyperspectral images, demonstrated the comparisons among these methods and pointed out the challenges that still exist.
Qingchen Qiu and Xuelian Wu contributed equally to this paper. This work was supported by the Fundamental Research Funds of Shandong University (No. 2015JC038).
Qiu, Q., Wu, X., Liu, Z., Tang, B., Zhao, Y., Wu, X., Zhu, H. and Xin, Y. (2017), "Survey of supervised classification techniques for hyperspectral images", Sensor Review, Vol. 37 No. 3, pp. 371-382. https://doi.org/10.1108/SR-07-2016-0124
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