Application of second generation wavelets to blind spherical deconvolution

Application of second generation wavelets to blind spherical deconvolution

We adress the problem of spherical deconvolution in a non parametric statistical framework, where both the signal and the operator kernel are subject to error measurements. After a preliminary treatment of the kernel, we apply a thresholding procedure to the signal in a second generation wavelet basis. Under standard assumptions on the kernel, we study the theoritical performance of the resulti...

Tackling mixed-phase wavelets in blind deconvolution using hybrid solver

By assuming the reflectivity series to be sparse rather than ”white”, we introduced the hybrid norm spiking deconvolution (Zhang, 2010). However one theoretical drawback of spiking deconvolution is that it assumes the source wavelet to be minimum-phase, which might not be true in practice. We propose a new formulation of spiking deconvolution with the hybrid solver that does not require such as...

Spherical Deconvolution

This paper proposes nonparametric deconvolution density estimation over S 2. Here we would think of the S 2 elements of interest being corrupted by random SO(3) elements (rotations). The resulting density on the observations would be a convolution of the SO(3) density with the true S 2 density. Consequently, the methodology, as in the Euclidean case, would be to use Fourier analysis on SO(3) an...

Poly-phase based blind deconvolution technique using second-order statistics

putational load numerical arithmetic such as a singular decomposition. A novel second-order statistics-based blind deconvolution and equalizer technique is proposed in this literature. This technique makes use of a two-channel perfect reconstruction jilter bank derived from a two-component polyphase decomposition of transmission channel in order to make exact system identifications possible. Th...

Localized spherical deconvolution