Feature detection from local energy
Pattern Recognition Letters
Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation Using Local Phase Differences in Gabor Filtered Images
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
A new class of two-channel biorthogonal filter banks and waveletbases
IEEE Transactions on Signal Processing
A filter bank for the directional decomposition of images: theoryand design
IEEE Transactions on Signal Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
3D fast spatial filtering method
International Journal of Computational Vision and Robotics
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In this article we consider the problem of automatic detection of curves, as opposed to straight lines, over a noisy image. We develop a two step model selection procedure based on a contourlet expansion of the image and prove the method is consistent in probability. The first step is based on usual threshold methods for frames. The second step selects pixels that spread energy over several simultaneous directions which is a known property of curve-like figures. We apply the proposed method to synthetic images and show its capability to separate curves from a noisy background and from a random collection of small straight lines. A practical application to seismic grids is also considered.