JOURNAL ARTICLE

A shadow detection method for remote sensing images using Affinity Propagation algorithm

Abstract

Shadow detection in high spatial resolution remote sensing image is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm in the Hue-Saturation-Intensity (HSI) color space. Because the pixel matrix is a large-scale matrix, if we apply AP algorithm directly on the raw pixel space, it will be computation intensive to calculate the similarity matrix. To solve this problem, we propose to divide the matrix into several blocks and then applying AP to detect shadows in H, S and I components respectively. Then, three detected images are fused to obtain a final shadow detection result. Comparative experiments are performed for K-means and threshold segmentation methods. The experimental results show that higher detection accuracy of the proposed approach is obtained, and it can solve the problems of false dismissals of K-means and threshold segmentation method.

Keywords:
Shadow (psychology) Pixel Computation Computer science Hue Artificial intelligence Computer vision Image segmentation Segmentation Algorithm Similarity (geometry) Matrix (chemical analysis) Image resolution Pattern recognition (psychology) Image (mathematics)

Metrics

17
Cited By
2.07
FWCI (Field Weighted Citation Impact)
20
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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