International audienceCosparse modeling is a recent alternative to sparse modeling, where the notion of dictionary is replaced by that of an analysis operator. When a known analysis operator is well adapted to describe the signals of interest, the model and associated algorithms can be used to solve inverse problems. Here we show how to derive an operator to model certain classes of signals that satisfy physical laws, such as the heat equation or the wave equation. We illustrate the approach on an acoustic inverse problem with a toy model of wave propagation and discuss its potential extensions and the challenges it raises
Inverse problems related to physical processes are of great importance in practically every field re...
International audienceRecently, a regularization framework for ill-posed inverse problems governed b...
International audienceThis paper investigates analysis operator learning for the recently introduced...
International audienceCosparse modeling is a recent alternative to sparse modeling, where the notion...
International audienceSolving an underdetermined inverse problem implies the use of a regularization...
International audienceSparse data models are powerful tools for solving ill-posed inverse problems. ...
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
Preprint available on arXiv since 24 Jun 2011International audienceAfter a decade of extensive study...
AbstractAfter a decade of extensive study of the sparse representation synthesis model, we can safel...
National audienceThis work aims at comparing several state-of-the-art methods for cosparse signal re...
International audienceIn the past decade there has been a great interest in a synthesis-based model ...
International audienceIn the past decade there has been a great interest in a synthesis-based model ...
International audienceRecently, a cosparse analysis model was introduced as an alternative to the st...
Inverse problems related to physical processes are of great importance in practically every field re...
International audienceRecently, a regularization framework for ill-posed inverse problems governed b...
International audienceThis paper investigates analysis operator learning for the recently introduced...
International audienceCosparse modeling is a recent alternative to sparse modeling, where the notion...
International audienceSolving an underdetermined inverse problem implies the use of a regularization...
International audienceSparse data models are powerful tools for solving ill-posed inverse problems. ...
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
Preprint available on arXiv since 24 Jun 2011International audienceAfter a decade of extensive study...
AbstractAfter a decade of extensive study of the sparse representation synthesis model, we can safel...
National audienceThis work aims at comparing several state-of-the-art methods for cosparse signal re...
International audienceIn the past decade there has been a great interest in a synthesis-based model ...
International audienceIn the past decade there has been a great interest in a synthesis-based model ...
International audienceRecently, a cosparse analysis model was introduced as an alternative to the st...
Inverse problems related to physical processes are of great importance in practically every field re...
International audienceRecently, a regularization framework for ill-posed inverse problems governed b...
International audienceThis paper investigates analysis operator learning for the recently introduced...