Orthogonal discrete periodic Radon transform. Part I: theory and realization

The discrete periodic Radon transform (DPRT) was proposed recently. It was shown that DPRT possesses many useful properties that are similar to the conventional continuous Radon transform. Using these properties, a 2-D signal can be processed by some 1-D approaches to reduce the computational complexity. However, the non-orthogonal structure of DPRT projections introduces redundant operations that often lower the efficiency of the technique in applications. In this paper, we propose the orthogonal discrete periodic Radon transform (ODPRT) in which a new decomposition approach is introduced. All ODPRT projections are modified to be orthogonal such that redundancy is eliminated. Furthermore, we consider the efficient realization for computing ODPRT and its inverse that make the proposed ODPRT more feasible in practical applications.

[1]  Yianni Attikiouzel,et al.  Fast computation of two-dimensional discrete cosine transforms using fast discrete radon transform , 1991 .

[2]  Chao Lu,et al.  Mathematics of Multidimensional Fourier Transform Algorithms , 1993 .

[3]  Vijay K. Madisetti,et al.  The fast discrete Radon transform. I. Theory , 1993, IEEE Trans. Image Process..

[4]  M. C. Jordan Traite des substitutions et des equations algebriques , 1870 .

[5]  Jorge L. C. Sanz,et al.  Radon and Projection Transform-Based Computer Vision: Algorithms, A Pipeline Architecture, and Industrial Applications , 1988 .

[6]  Elias S. Manolakos,et al.  A new approach for computing multidimensional DFT's on parallel machines and its implementation on the iPSC/860 hypercube , 1995, IEEE Trans. Signal Process..

[7]  Tai-Chiu Hsung,et al.  Orthogonal discrete periodic Radon transform. Part II: applications , 2003, Signal Process..

[8]  Izidor Gertner A new efficient algorithm to compute the two-dimensional discrete Fourier transform , 1988, IEEE Trans. Acoust. Speech Signal Process..

[9]  Jorge L. C. Sanz,et al.  Radon and projection transform-based computer vision , 1988 .

[10]  Wan-Chi Siu,et al.  On the convolution property of a new discrete Radon transform and its efficient inversion algorithm , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.

[11]  Dekun Yang Fast discrete radon transform and 2-D discrete Fourier transform , 1990 .

[12]  Jaakko Astola,et al.  New fast algorithms of multidimensional Fourier and Radon discrete transforms , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[13]  Gregory Beylkin,et al.  Discrete radon transform , 1987, IEEE Trans. Acoust. Speech Signal Process..

[14]  Jaakko Astola,et al.  Fast algorithms of multidimensional discrete nonseparable -wave transforms , 2002, IEEE Trans. Signal Process..

[15]  J. R. Resnick The radon transforms and some of its applications , 1985, IEEE Trans. Acoust. Speech Signal Process..

[16]  Jan Flusser,et al.  Image Representation Via a Finite Radon Transform , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Wan-Chi Siu,et al.  The discrete periodic Radon transform , 1996, IEEE Trans. Signal Process..

[18]  Michael Vulis The weighted redundancy transform , 1989, IEEE Trans. Acoust. Speech Signal Process..

[19]  Ethan D. Bolker,et al.  The finite Radon transform , 1987 .

[20]  Wan-Chi Siu,et al.  On the efficient computation of 2-d image moments using the discrete radon transform , 1998, Pattern Recognit..

[21]  Yang Dekun Fast computation of two-dimensional discrete Fourier transform using fast discrete Radon transform , 1990, IEEE TENCON'90: 1990 IEEE Region 10 Conference on Computer and Communication Systems. Conference Proceedings.

[22]  Tai-Chiu Hsung,et al.  Efficient blind blur identification using discrete periodic Radon transform , 2001, Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489).

[23]  D. W. Lin,et al.  Nonlinear quantisation of spectral shape in sub-band coding , 1989 .

[24]  Elias S. Manolakos,et al.  A New Approach for Computing Multi-dimensional Dfts on Parallel Machines and Its Implementation on the Ipsc/860 Hypercube Sp-edics 4.1.5 Multidimensional Signal Processing: System Architectures and Implementations 2.2.7 Fast Algorithms: Algorithm Implementation in Hardware and Software , 1995 .

[25]  Minh N. Do,et al.  Orthonormal finite ridgelet transform for image compression , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[26]  D.P.-K. Lun,et al.  An improved fast Radon transform algorithm for two-dimensional discrete Fourier and Hartley transform , 1992, [Proceedings] 1992 IEEE International Symposium on Circuits and Systems.

[27]  I. Gertner,et al.  Fast Algorithms To Compute Multidimensional Discrete Fourier Transform , 1989, Optics & Photonics.

[28]  Izidor Gertner,et al.  VLSI Architectures for Multidimensional Fourier Transform Processing , 1987, IEEE Transactions on Computers.