Sub-Hexagonal Phase Correlation for Motion Estimation

We present a novel frequency-domain motion estimation technique, which operates on hexagonal images and employs the hexagonal Fourier transform. Our method involves image sampling on a hexagonal lattice followed by a normalised hexagonal cross-correlation in the frequency domain. The term subpixel (or subcell) is defined on a hexagonal grid in order to achieve floating point registration. Experiments using both artificially induced motion and actual motion demonstrate that the proposed method outperforms the state-of-the-art in frequency-domain motion estimation operating on a square lattice, in the shape of phase correlation, in terms of subpixel accuracy for a range of test material and motion scenarios.

[1]  Hassan Foroosh,et al.  Extension of phase correlation to subpixel registration , 2002, IEEE Trans. Image Process..

[2]  Qingtang Jiang,et al.  Orthogonal and Biorthogonal FIR Hexagonal Filter Banks With Sixfold Symmetry , 2008, IEEE Transactions on Signal Processing.

[3]  G. A. Thomas,et al.  Television motion measurement for DATV and other applications , 1987 .

[4]  R.M. Mersereau,et al.  The processing of hexagonally sampled two-dimensional signals , 1979, Proceedings of the IEEE.

[5]  Vasileios Argyriou,et al.  A Study of Sub-pixel Motion Estimation using Phase Correlation , 2006, BMVC.

[6]  Neil Storey,et al.  A Comparison Between Square and Hexagonal Sampling Methods for Pipeline Image Processing , 1990, Other Conferences.

[7]  Andrew F. Laine,et al.  Hexagonal wavelet representations for recognizing complex annotations , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[8]  L. J. Cutrona,et al.  The Processing of Hexagonally Sampled Two-Dimensional Signals , 1979 .

[9]  V. N. Dvornychenko,et al.  Bounds on (Deterministic) Correlation Functions with Application to Registration , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Bryan W. Scotney,et al.  Fast Multiscale Operator Development for Hexagonal Images , 2009, DAGM-Symposium.

[11]  William Scott Hoge,et al.  A subspace identification extension to the phase correlation method [MRI application] , 2003, IEEE Transactions on Medical Imaging.

[12]  Ardeshir Goshtasby,et al.  A Region-Based Approach to Digital Image Registration with Subpixel Accuracy , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[14]  R. C. Staunton,et al.  One-pass parallel hexagonal thinning algorithm , 2001 .

[15]  Bernd Girod,et al.  Motion-compensating prediction with fractional-pel accuracy , 1993, IEEE Trans. Commun..

[16]  David Middleton,et al.  Sampling and Reconstruction of Wave-Number-Limited Functions in N-Dimensional Euclidean Spaces , 1962, Inf. Control..

[17]  Rik Van de Walle,et al.  Accepted for Publication in Ieee Transactions on Image Processing Hex-splines: a Novel Spline Family for Hexagonal Lattices , 2022 .

[18]  C. D. Kuglin,et al.  Video-Rate Image Correlation Processor , 1977, Optics & Photonics.

[19]  Denis White,et al.  Cartographic and Geometric Components of a Global Sampling Design for Environmental Monitoring , 1992 .

[20]  Michael T. Orchard,et al.  A fast direct Fourier-based algorithm for subpixel registration of images , 2001, IEEE Trans. Geosci. Remote. Sens..

[21]  Qingtang Jiang,et al.  Hexagonal tight frame filter banks with idealized high-pass filters , 2009, Adv. Comput. Math..

[22]  Masayuki Nakajima,et al.  Design and Evaluation of More Accurate Gradient Operators on Hexagonal Lattices , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  R. Gordon,et al.  Comparison of square-pixel and hexagonal-pixel resolution in image processing , 2002, IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No.02CH37373).

[24]  Alessandro Verri,et al.  Against Quantitative Optical Flow , 1987 .

[25]  Michael J. Black,et al.  The Dense Estimation of Motion and Appearance in Layers , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[26]  Q. Jiang,et al.  FIR Filter Banks for Hexagonal Data Processing , 2008, IEEE Transactions on Image Processing.

[27]  Marcel Worring,et al.  Dense motion estimation using regularization constraints on local parametric models , 2004, IEEE Transactions on Image Processing.

[28]  Jian Fan,et al.  Mammographic feature enhancement by multiscale analysis , 1994, IEEE Trans. Medical Imaging.

[29]  Xiangjian He,et al.  Hexagonal Structure for Intelligent Vision , 2005 .

[30]  Qi Tian,et al.  Algorithms for subpixel registration , 1986 .

[31]  Eric C. Olson,et al.  A geometric approach to subpixel registration accuracy , 1987, Computer Vision Graphics and Image Processing.

[32]  Vasileios Argyriou,et al.  Using gradient correlation for sub-pixel motion estimation of video sequences , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[33]  Jayanthi Sivaswamy,et al.  Hexagonal Image Processing: A Practical Approach , 2014, Advances in Pattern Recognition.

[34]  Richard C. Staunton,et al.  The design of hexagonal sampling structures for image digitization and their use with local operators , 1989, Image Vis. Comput..

[35]  Jayanthi Sivaswamy,et al.  Edge detection in a hexagonal-image processing framework , 2001, Image Vis. Comput..

[36]  K. Sahr,et al.  Geodesic Discrete Global Grid Systems , 2003 .

[37]  Ikram E. Abdou,et al.  Practical approach to the registration of multiple frames of video images , 1998, Electronic Imaging.

[38]  James C. Ehrhardt Hexagonal fast Fourier transform with rectangular output , 1993, IEEE Trans. Signal Process..

[39]  Michael Spann,et al.  Robust optical flow estimation based on a sparse motion trajectory set , 2003, IEEE Trans. Image Process..

[40]  R. J. Green,et al.  Fingerprint classification using a hexagonal fast fourier transform , 1996, Pattern Recognit..