JOURNAL ARTICLE

Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means

Xin WangJing HuangYanli ChuAiye ShiLizhong Xu

Year: 2018 Journal:   KSII Transactions on Internet and Information Systems Vol: 12 (4)   Publisher: Korea Society of Internet Information

Abstract

Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis.This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM).Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task.The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image.The proposed method has been validated on real bitemporal remote sensing data sets.Experimental results confirmed the effectiveness of the proposed method.

Keywords:
Computer science Change detection Fuzzy logic Feature (linguistics) Artificial intelligence Computer vision Pattern recognition (psychology) Fusion Remote sensing Data mining Geology

Metrics

8
Cited By
0.88
FWCI (Field Weighted Citation Impact)
26
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
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