Self-Invertible 2D Log-Gabor Wavelets
International Journal of Computer Vision
Sparse approximation of images inspired from the functional architecture of the primary visual areas
EURASIP Journal on Applied Signal Processing
Sparse coding via thresholding and local competition in neural circuits
Neural Computation
Bayesian marginal statistics for speech enhancement using log Gabor wavelet
International Journal of Speech Technology
An Expert Support System for Breast Cancer Diagnosis using Color Wavelet Features
Journal of Medical Systems
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Gabor representations present a number of interesting properties despite the fact that the basis functions are nonorthogonal and provide an overcomplete representation or a nonexact reconstruction. Overcompleteness involves an expansion of the number of coefficients in the transform domain and induces a redundancy that can be further reduced through computational costly iterative algorithms like Matching Pursuit. Here, a biologically plausible algorithm based on competitions between neighboring coefficients is employed for adaptively representing any source image by a selected subset of Gabor functions. This scheme involves a sharper edge localization and a significant reduction of the information redundancy, while, at the same time, the reconstruction quality is preserved. The method is characterized by its biological plausibility and promising results, but it still requires a more in depth theoretical analysis for completing its validation.