Tracking hand and finger movements for behaviour analysis
Pattern Recognition Letters
Tracking hand and finger movements for behaviour analysis
Pattern Recognition Letters - Special issue on vision for crime detection and prevention
Extrapolative Spatial Models for Detecting Perceptual Boundaries in Colour Images
International Journal of Computer Vision
A survey of architecture and function of the primary visual cortex (V1)
EURASIP Journal on Applied Signal Processing
Support vector regression based image denoising
Image and Vision Computing
Image and video denoising using adaptive dual-tree discrete wavelet packets
IEEE Transactions on Circuits and Systems for Video Technology
Wavelet steerability and the higher-order Riesz transform
IEEE Transactions on Image Processing
Steerable weighted median filters
IEEE Transactions on Image Processing
Document image analysis: issues, comparison of methods and remaining problems
Artificial Intelligence Review
Journal of Biomedical Imaging
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This work addresses the design of a novel complex steerable wavelet construction, the generation of transform-space feature measurements associated with corner and edge presence and orientation properties, and the application of these measurements directly to image denoising. The decomposition uses pairs of bandpass filters that display symmetry and antisymmetry about a steerable axis of orientation. While the angular characterization of the bandpass filters is similar to those previously described, the radial characteristic is new, as is the manner of constructing the interpolation functions for steering. The complex filters have been engineered into a multirate system, providing a synthesis and analysis subband filtering system with good reconstruction properties. Although the performance of our proposed denoising strategy is currently below that of recently reported state-of-the-art techniques in denoising, it does compare favorably with wavelet coring approaches employing global thresholds and with an "Oracle" shrinkage technique, and presents a very promising avenue for exploring structure-based denoising in the wavelet domain.