JOURNAL ARTICLE

A Soft Shadow Detection Method Based on MRF for Remote Sensing Images

Pengwei LiWenying Ge

Year: 2015 Journal:   Mathematical Problems in Engineering Vol: 2015 Pages: 1-11   Publisher: Hindawi Publishing Corporation

Abstract

Shadows limit many remote sensing applications such as classification, target detection, and change detection. Most current shadow detection methods utilize the histogram threshold of spectral characteristics to distinguish the shadows and nonshadows directly, called “hard binary shadow.” Obviously, the performance of threshold-based methods heavily rely on the selected threshold. Simultaneously, these threshold-based methods do not take any spatial information into account. To overcome these shortcomings, a soft shadow description method is developed by introducing the concept of opacity into shadow detection, and MRF-based shadow detection method is proposed in order to make use of neighborhood information. Experiments on remote sensing images have shown that the proposed method can obtain more accurate detection results.

Keywords:
Shadow (psychology) Histogram Computer science Artificial intelligence Computer vision Limit (mathematics) Binary number Image (mathematics) Remote sensing Pattern recognition (psychology) Mathematics Geography

Metrics

5
Cited By
0.00
FWCI (Field Weighted Citation Impact)
14
Refs
0.05
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

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