Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, but most of them are limited by a heavy computationalcost and by difficulties to find the optimal solutions. We proposehere an algorithm suitable for Gabor wavelets and based onbiological models. It is composed by local operations betweenneighboring transform coefficients and achieves a sparserepresentation with a relatively low computational cost. Used with achain coder, this sparse Gabor wavelet transform is suitable forimage compression but is also of interest also for otherapplications, in particular for edge and contour extraction andimage denoising.