Abstract
An approach for effective implementation of greedy selection methodologies, to approximate an image partitioned into blocks, is proposed. The method is specially designed for approximating partitions on a transformed image. It evolves by selecting, at each iteration step, i) the elements for approximating each of the blocks partitioning the image and ii) the hierarchized sequence in which the blocks are approximated to reach the required global condition on sparsity.
| Original language | English |
|---|---|
| Pages (from-to) | 1175-1178 |
| Number of pages | 4 |
| Journal | IEEE Signal Processing Letters |
| Volume | 20 |
| Issue number | 12 |
| Early online date | 8 Oct 2013 |
| DOIs | |
| Publication status | Published - Dec 2013 |
Bibliographical note
© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software for implementing the approach is available on http://www.nonlinear-approx.info/examples/node0.html
Funding: EPSRC
Keywords
- high quality sparse image approximation with separable dictionaries
- orthogonal matching pursuit for sparse representation of partitions in the wavelet domain