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ISPRS annals of the photogrammetry, remote sensing and spatial information sciences • Vol V-3-2020
EARTHQUAKE-DAMAGED REGIONS DETECTION FROM HIGH RESOLUTION IMAGE BASED ON SUPER-PIXEL SEGMENTATION AND DEEP LEARNING
August 2020 • C. Liu, Haigang Sui, Peng Yan, Hua Li, Qinghua Li
Abstract. Accurate detection and automatic processing of earthquake-damaged regions is essential for effective rescue and post-disaster reconstruction. In this study, we proposed a Combined Super-pixel Segmentation and AlexNet Detection approach (CSSAD) for automatically extracting damaged regions from post-earthquake high-resolution images. Simple Linear Iterative Clustering (SLIC) algorithm was used to segment the high resolution images to obtain more homogeneous geo-objects. Multiscale samples database, which t…
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Computer Science
Artificial Intelligence
Pixel
Segmentation Fault
Computer Vision
Cluster Analysis
Image Resolution
Image Segmentation
Remote Sensing
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