Exploiting joint sparsity information by coupled Bregman iterations
Seminar Room 1, Newton Institute
AbstractCo-authors: Eva-Maria Brinkmann (WWU Münster), Michael Möller (Arnold & Richter Cinetechnik), Tamara Seybold (Arnold & Richter Cinetechnik)
Many applications are concerned with the reconstruction or denoising of multichannel images (color, spectral, time) with a natural prior information of correlated sparsity patterns. The most striking one is joint edge sparsity for different channels of a color image.
We discuss how such prior information can be encoded in Bregman distances for frequently used one-homogeneous functionals, and introduce a novel concept of infimal convolution of Bregman distances. We then discuss appropriate modifications of Bregman iterations towards a coupled reconstruction scheme. First results are presented for color image denoising.
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