Sparse Gabor wavelets by local operations

Efficient sparse coding of overcomplete transforms remains still an open problem. Different methods have been proposed in the literature, but most of them are limited by a heavy computational cost and by difficulties to find the optimal solutions. We propose here an algorithm suitable for Gabor wavelets and based on biological models. It is composed by local operations between neighboring transform coefficients and achieves a sparse representation with a relatively low computational cost. Used with a chain coder, this sparse Gabor wavelet transform is suitable for image compression but is also of interest also for other applications, in particular for edge and contour extraction and image denoising.

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