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Remote Sens. 2017, 9(8), 773; https://doi.org/10.3390/rs9080773

Improving Super-Resolution Mapping by Combining Multiple Realizations Obtained Using the Indicator-Geostatistics Based Method

1
Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Minerals, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
3
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
4
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
5
Migu Digital Media Co. Ltd., Hangzhou 310030, China
*
Author to whom correspondence should be addressed.
Received: 5 June 2017 / Revised: 9 July 2017 / Accepted: 25 July 2017 / Published: 28 July 2017
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Abstract

Indicator-geostatistics based super-resolution mapping (IGSRM) is a popular super-resolution mapping (SRM) method. Unlike most existing SRM methods that produce only one SRM result each, IGSRM generates multiple equally plausible super-resolution realizations (i.e., SRM results). However, multiple super-resolution realizations are not desirable in many applications, where only one SRM result is usually required. These super-resolution realizations may have different strengths and weaknesses. This paper proposes a novel two-step combination method of generating a single SRM result from multiple super-resolution realizations obtained by IGSRM. In the first step of the method, a constrained majority rule is proposed to combine multiple super-resolution realizations generated by IGSRM into a single SRM result under the class proportion constraint. In the second step, partial pixel swapping is proposed to further improve the SRM result obtained in the previous step. The proposed combination method was evaluated for two study areas. The proposed method was quantitatively compared with IGSRM and Multiple SRM (M-SRM), an existing multiple SRM result combination method, in terms of thematic accuracy and geometric accuracy. Experimental results show that the proposed method produces SRM results that are better than those of IGSRM and M-SRM. For example, in the first example, the overall accuracy of the proposed method is 7.43–10.96% higher than that of the IGSRM method for different scale factors, and 1.09–3.44% higher than that of the M-SRM, while, in the second example, the improvement in overall accuracy is 2.42–4.92%, and 0.08–0.90%, respectively. The proposed method provides a general framework for combining multiple results from different SRM methods. View Full-Text
Keywords: super-resolution mapping; indicator geostatistics; class proportion constraint; pixel swapping; land cover classification super-resolution mapping; indicator geostatistics; class proportion constraint; pixel swapping; land cover classification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Shi, Z.; Li, P.; Jin, H.; Tian, Y.; Chen, Y.; Zhang, X. Improving Super-Resolution Mapping by Combining Multiple Realizations Obtained Using the Indicator-Geostatistics Based Method. Remote Sens. 2017, 9, 773.

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