AISIR: Automated inter-sensor/inter-band satellite image registration using robust complex wavelet feature representations

Authors:
Alexander Wong;David A. Clausi
Affiliations:
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1;Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1
Venue:
Pattern Recognition Letters
Year:
2010

Citing 10
Cited 2

Alignment by Maximization of Mutual Information

International Journal of Computer Vision
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
Multiple view geometry in computer vision

Multiple view geometry in computer vision
The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Automatic Mosaicing with Super-Resolution Zoom

CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Fast communication: Adaptive bilateral filtering of image signals using local phase characteristics

Signal Processing
An Iterative Approach to Improved Local Phase Coherence Estimation

CRV '08 Proceedings of the 2008 Canadian Conference on Computer and Robot Vision
Efficient global weighted least-squares translation registration in the frequency domain

ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient

IEEE Transactions on Image Processing
Efficient Least Squares Multimodal Registration With a Globally Exhaustive Alignment Search

IEEE Transactions on Image Processing

Image-Based Attitude Control of a Remote Sensing Satellite

Journal of Intelligent and Robotic Systems
Local joint entropy based non-rigid multimodality image registration

Pattern Recognition Letters

Quantified Score

Hi-index	0.10

Visualization

Abstract

An automated registration system named AISIR (Automated inter-sensor/inter-band satellite image registration) has been designed and implemented for the purpose of registering satellite images acquired using different sensors and spectral bands. Sensor and environmental noise, contrast non-uniformities, and inter-sensor and inter-band intensity mapping differences are addressed in the AISIR system. First, a novel modified Geman-McClure M-estimation scheme using a robust phase-adaptive complex wavelet feature representation is introduced for robust control point matching. Second, an iterative refinement scheme is introduced in the AISIR system for improved control point pair localization. Finally, the AISIR system introduces a robust mapping function estimation scheme based on the proposed modified Geman-McClure M-estimation scheme. The AISIR system was tested using various multi-spectral optical, LIDAR, and SAR images and was shown to achieve better registration accuracy than state-of-the-art M-SSD and ARRSI registration algorithms for all of the test sets.