Cosparse dictionary learning for the orthogonal case
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2015 19th International Conference on System Theory, Control and Computing, ICSTCC 2015 - Joint Conference SINTES 19, SACCS 15, SIMSIS 19 |
| Publisher | IEEE |
| Pages | 343-347 |
| Number of pages | 5 |
| ISBN (Print) | 9781479984817 |
| DOIs | |
| Publication status | Published - 5 Nov 2015 |
| Publication type | A4 Article in a conference publication |
| Event | International conference on system theory, control and computing - Duration: 1 Jan 2014 → … |
Conference
| Conference | International conference on system theory, control and computing |
|---|---|
| Period | 1/01/14 → … |
Abstract
Dictionary learning is usually approached by looking at the support of the sparse representations. Recent years have shown results in dictionary improvement by investigating the cosupport via the analysis-based cosparse model. In this paper we present a new cosparse learning algorithm for orthogonal dictionary blocks that provides significant dictionary recovery improvements and representation error shrinkage. Furthermore, we show the beneficial effects of using this algorithm inside existing methods based on building the dictionary as a structured union of orthonormal bases.
ASJC Scopus subject areas
Keywords
- cosparse, dictionary design, orthogonal blocks, sparse representation