Phase correlation pixel-to-pixel image co-registration based on optical flow and median shift propagation

Authors:
J. G. Liu;H. Yan
Affiliations:
Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK;Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
Venue:
International Journal of Remote Sensing
Year:
2008

Citing 6
Cited 0

Performance of optical flow techniques

International Journal of Computer Vision
Digital video processing

Digital video processing
Estimating Optical Flow in Segmented Images Using Variable-Order Parametric Models With Local Deformations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Remote Sensing, Third Edition: Models and Methods for Image Processing

Remote Sensing, Third Edition: Models and Methods for Image Processing
An FFT-based technique for translation, rotation, and scale-invariant image registration

IEEE Transactions on Image Processing
Extension of phase correlation to subpixel registration

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

With singular value decomposition (SVD) and robust 2-dimensional fitting phase correlation algorithms, it is possible to achieve pixel-to-pixel image co-registration at sub-pixel accuracy via local feature matching. However, the method often fails in featureless and low correlation areas making it not robust for co-registration of images with considerable spectral differences and large featureless ground objects. A median shift propagation (MSP) technique is proposed to eliminate the problem, in a phase correlation and Normalized Cross-Correlation (NCC) combined approach. The experiment results using images from different sensor platforms and spectral bands indicate that the new method is very robust to featureless and low correlation areas and can achieve very accurate pixel-to-pixel image co-registration with good tolerance of spectral and spatial differences between images. The method will significantly improve change detection in various remote sensing applications.