IEEE Trans Image Process - 3D steerable wavelets in practice.

Tópicos

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Resumo

We introduce a systematic and practical design for steerable wavelet frames in 3D. Our steerable wavelets are obtained by applying a 3D version of the generalized Riesz transform to a primary isotropic wavelet frame. The novel transform is self-reversible (tight frame) and its elementary constituents (Riesz wavelets) can be efficiently rotated in any 3D direction by forming appropriate linear combinations. Moreover, the basis functions at a given location can be linearly combined to design custom (and adaptive) steerable wavelets. The features of the proposed method are illustrated with the processing and analysis of 3D biomedical data. In particular, we show how those wavelets can be used to characterize directional patterns and to detect edges by means of a 3D monogenic analysis. We also propose a new inverse-problem formalism along with an optimization algorithm for reconstructing 3D images from a sparse set of wavelet-domain edges. The scheme results in high-quality image reconstructions which demonstrate the feature-reduction ability of the steerable wavelets as well as their potential for solving inverse problems.

Resumo Limpo

introduc systemat practic design steerabl wavelet frame d steerabl wavelet obtain appli d version general riesz transform primari isotrop wavelet frame novel transform selfrevers tight frame elementari constitu riesz wavelet can effici rotat d direct form appropri linear combin moreov basi function given locat can linear combin design custom adapt steerabl wavelet featur propos method illustr process analysi d biomed data particular show wavelet can use character direct pattern detect edg mean d monogen analysi also propos new inverseproblem formal along optim algorithm reconstruct d imag spars set waveletdomain edg scheme result highqual imag reconstruct demonstr featurereduct abil steerabl wavelet well potenti solv invers problem

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