JOURNAL ARTICLE

Object-oriented multi-feature fusion change detection method for high resolution remote sensing image

Abstract

High resolution satellite images offer abundance information of the earth surface for remote sensing applications. For two decades, the detection and monitoring of change using high resolution satellite images has been a topic of interest in remote sensing. Recent investigations have shown that the pixel-based analysis of change detection for high resolution images has explicit limits. Using object-based techniques some problems of pixel-based image analysis could be overcome. In this paper, a novel object-oriented change detection method for high resolution image using multi-feature fusion is introduced. The main steps of this method are :segment the image, choose optimized features from spectral features, texture features, shape features of the segment objects, use optimized features to do change detection, make fusion of the preliminary change detection results of the different optimized features to get the final result. Experiments show that the method has a stronger advantage than the traditional pixel-level methods for high resolution remote sensing image change detection.

Keywords:
Change detection Computer science Artificial intelligence Image fusion Computer vision Pixel Feature (linguistics) Remote sensing Image resolution Feature detection (computer vision) Object detection Feature extraction High resolution Fusion Image (mathematics) Pattern recognition (psychology) Image processing Geography

Metrics

11
Cited By
0.00
FWCI (Field Weighted Citation Impact)
13
Refs
0.17
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
Remote Sensing in Agriculture
Physical Sciences →  Environmental Science →  Ecology

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