JOURNAL ARTICLE

Multi-Modal Remote Sensing Image Registration Based on Multi-Scale Phase Congruency

Abstract

Automatic matching of multi-modal remote sensing images remains a challenging task in remote sensing image analysis due to significant non-linear radiometric differences between these images. This paper introduces the phase congruency model with illumination and contrast invariance for image matching, and extends the model to a novel image registration method, named as multi-scale phase consistency (MS-PC). The Euclidean distance between MS-PC descriptors is used as similarity metric to achieve correspondences. The proposed method is evaluated with four pairs of multi-model remote sensing images. The experimental results show that MS-PC is more robust to the radiation differences between images, and performs better than two popular method (i.e. SIFT and SAR-SIFT) in both registration accuracy and tie points number.

Keywords:
Phase congruency Scale-invariant feature transform Artificial intelligence Computer vision Computer science Image registration Metric (unit) Euclidean distance Similarity (geometry) Matching (statistics) Modal Scale (ratio) Homography Consistency (knowledge bases) Pattern recognition (psychology) Remote sensing Image (mathematics) Mathematics Geography

Metrics

11
Cited By
0.72
FWCI (Field Weighted Citation Impact)
22
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Infrared Target Detection Methodologies
Physical Sciences →  Engineering →  Aerospace Engineering

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