On the Inverse Hough Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Blind Image Restoration Based on 1-D Generalized Cross Validation
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Orthogonal discrete periodic Radon transform: part II: applications
Signal Processing
Generalized Discrete Radon Transforms and Their Use in the Ridgelet Transform
Journal of Mathematical Imaging and Vision
Orthogonal discrete radon transform over pn × pnimages
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Generalised finite radon transform for N x N images
Image and Vision Computing
A new digital implementation of ridgelet transform for images of dyadic length
Journal of Network and Computer Applications
Comments on "The discrete periodic radon transform"
IEEE Transactions on Signal Processing
Reply to "Comments on 'The discrete periodic radon transform'"
IEEE Transactions on Signal Processing
Comments on “Generalised finite Radon transform for N × N images”
Image and Vision Computing
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
A discrete modulo N projective radon transform for N × N images
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
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In this correspondence, a discrete periodic Radon transform and its inversion are developed. The new discrete periodic Radon transform possesses many properties similar to the continuous Radon transform such as the Fourier slice theorem and the convolution property, etc. With the convolution property, a 2-D circular convolution can be decomposed into 1-D circular convolutions, hence improving the computational efficiency. Based on the proposed discrete periodic Radon transform, we further develop the inversion formula using the discrete Fourier slice theorem. It is interesting to note that the inverse transform is multiplication free. This important characteristic not only enables fast inversion but also eliminates the finite-word-length error that may be generated in performing the multiplications