Fast cross-spectral image registration using new robust correlation

In this paper, we explore a new correlation technique for cross-spectral image registration. The proposed technique matches the orientation feature of the second derivatives while making use of a statistical robust M estimator. Furthermore, it takes advantage of Fourier and multi-resolution techniques to reduce the complexity of spatial correlation. Simulation results show that our proposed approach gives more accurate results than the mutual information, and the normalized cross-correlation with prefiltering in terms of speed and accuracy.

[1]  G. Marchal,et al.  Multi-modal volume registration by maximization of mutual information , 1997 .

[2]  A. Bijaoui,et al.  Geometrical registration of images: the multiresolution approach , 1993 .

[3]  P. Anandan,et al.  About Direct Methods , 1999, Workshop on Vision Algorithms.

[4]  Peter J. Huber,et al.  Robust Statistics , 2005, Wiley Series in Probability and Statistics.

[5]  Jacqueline Le Moigne,et al.  Application of rotation- and translation-invariant overcomplete wavelets to the registration of remotely sensed imagery , 1999, Defense, Security, and Sensing.

[6]  Harold S. Stone,et al.  Blind cross-spectral image registration using prefiltering and Fourier-based translation detection , 2002, IEEE Trans. Geosci. Remote. Sens..

[7]  C. D. Kuglin,et al.  The phase correlation image alignment method , 1975 .

[8]  J. L. Moigne.  Parallel registration of multisensor remotely sensed imagery using wavelet coefficients , 1994 .

[9]  C. Morandi,et al.  Registration of Translated and Rotated Images Using Finite Fourier Transforms , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Jacqueline Le Moigne,et al.  Use of wavelets for image registration , 2000, SPIE Defense + Commercial Sensing.

[11]  Michal Irani,et al.  All About Direct Methods , 1999 .

[12]  Charles V. Stewart,et al.  Robust hierarchical algorithm for constructing a mosaic from images of the curved human retina , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[13]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[14]  Jacqueline LeMoigne,et al.  Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery , 1997 .

[15]  James S. Walker.  Fast Fourier Transforms , 1991 .

[16]  Michael Unser,et al.  A pyramid approach to subpixel registration based on intensity , 1998, IEEE Trans. Image Process..

[17]  Michael Unser,et al.  Optimization of mutual information for multiresolution image registration , 2000, IEEE Trans. Image Process..

[18]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[19]  P. Anandan,et al.  Robust multi-sensor image alignment , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[20]  K. Mardia,et al.  A review of image-warping methods , 1998 .

[21]  R. J. Althof,et al.  A rapid and automatic image registration algorithm with subpixel accuracy , 1997, IEEE Transactions on Medical Imaging.

[22]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[23]  K. Mardia,et al.  A penalized likelihood approach to image warping , 2001 .

[24]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[25]  J. Le Moigne,et al.  Towards a parallel registration of multiple resolution remote sensing data , 1995 .

[26]  D. F. Andrews,et al.  Robust Estimates of Location: Survey and Advances. , 1975 .

[27]  William J. Christmas,et al.  Orientation Correlation , 2002, BMVC.

[28]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[29]  William J. Christmas,et al.  Structural Matching in Computer Vision Using Probabilistic Relaxation , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  C. J. Lawrence.  Robust estimates of location : survey and advances , 1975 .

[31]  Zhengwei Yang,et al.  Image registration and object recognition using affine invariants and convex hulls , 1999, IEEE Trans. Image Process..

[32]  Christopher Justice,et al.  The impact of misregistration on change detection , 1992, IEEE Trans. Geosci. Remote. Sens..

[33]  S. Iyengar,et al.  Multi-Sensor Fusion: Fundamentals and Applications With Software , 1997 .

[34]  David Casasent,et al.  Optical correlation filter fusion for object detection , 1994 .

[35]  S. P. Kim,et al.  Subpixel accuracy image registration by spectrum cancellation , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[36]  Robert A. Schowengerdt,et al.  Remote sensing, models, and methods for image processing , 1997 .

[37]  Michael Unser,et al.  A pyramid approach to sub-pixel image fusion based on mutual information , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[38]  Yoram Bresler,et al.  Recursive image registration with application to motion estimation , 1987, IEEE Trans. Acoust. Speech Signal Process..

[39]  Morgan McGuire,et al.  Techniques for multiresolution image registration in the presence of occlusions , 2000, IEEE Trans. Geosci. Remote. Sens..