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http://hdl.handle.net/10397/77863
Title: | Accuracy assessment measures for object extraction from remote sensing images | Authors: | Cai, L Shi, W Miao, Z Hao, M |
Issue Date: | 2018 | Source: | Remote sensing, Feb. 2018, v. 10, no. 2, 303, p. 1-13 | Abstract: | Object extraction from remote sensing images is critical for a wide range of applications, and object-oriented accuracy assessment plays a vital role in guaranteeing its quality. To evaluate object extraction accuracy, this paper presents several novel accuracy measures that differ from the norm. First, area-based and object number-based accuracy assessment measures are given based on a confusion matrix. Second, different accuracy assessment measures are provided by combining the similarities of multiple features. Third, to improve the reliability of the object extraction accuracy assessment results, two accuracy assessment measures based on object detail differences are designed. In contrast to existing measures, the presented method synergizes the feature similarity and distance difference, which considerably improves the reliability of object extraction evaluation. Encouraging results on two QuickBird images indicate the potential for further use of the presented algorithm. | Keywords: | Accuracy assessment Distance difference Feature similarity Object-based image analysis |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | Remote sensing | EISSN: | 2072-4292 | DOI: | 10.3390/rs10020303 | Rights: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The following publication Cai, L.; Shi, W.; Miao, Z.; Hao, M. Accuracy Assessment Measures for Object Extraction from Remote Sensing Images. Remote Sens. 2018, 10, 2, 303,1-13 is available at https://dx.doi.org/10.3390/rs10020303 |
Appears in Collections: | Journal/Magazine Article |
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Cai_Accuracy_Remote_Sensing.pdf | 1.69 MB | Adobe PDF | View/Open |
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