| Autor: |
Yangyang Chen, Dongping Ming, Lu Zhao, Beiru Lv, Keqi Zhou, Yuanzhao Qing |
| Předmět: |
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| Zdroj: |
Photogrammetric Engineering & Remote Sensing; Oct2018, Vol. 84 Issue 10, p629-646, 18p |
| Abstrakt: |
Image segmentation is a key technique involved in information extraction from high spatial resolution remote sensing images. Studying the impact of the evaluation method on the segmentation result is equally as important as studying the segmentation algorithm itself. However, research in segmentation evaluation is behind that of segmentation algorithms. Only a few review articles about segmentation evaluation were published in computer vision field. Therefore, reviewing segmentation evaluation methods used for high spatial resolution remote sensing images is of great significance. This paper summarizes widely used evaluation methods in remote sensing field, analyzes their advantages and shortcomings, and discusses their application range. Especially this paper uses series of experiments to demonstrate the supervised and unsupervised image segmentation evaluation process and analyzes the performance of some commonly used supervised and unsupervised evaluation indexes. Further, potential applications and possible future direction for high spatial resolution remote sensing image segmentation evaluation are finally summarized. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
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