Rotation- and scale-invariant texture classification using log-polar and ridgelet transforms
Machine Graphics & Vision International Journal
Face recognition in 2D and 2.5D using ridgelets and photometric stereo
Pattern Recognition
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Ridgelet transform is a new directional multi-resolution transform and it is more suitable for describing the signals with line or super-plane singularities. Finite ridgelet transform is a discrete orthonormal version of ridgelet transform proposed by Minh N. Do and Martin Vetterli [5]. However, finite ridgelet transform is only suitable for images of prime-pixels length, which is a limitation of its application in image processing. In this paper, we improve the finite ridgelet algorithm and a new digital implementation of ridgelet transform which is suitable for images of dyadic length is proposed. This method not only keeps the main properties of finite ridgelet but also simplifies the algorithm. We first briefly introduce the concept of ridgelet transform. Then, we illustrate finite ridgelet transform and the new method. Finally, we compare the new method with traditional finite ridgelet transform.