Hierarchized block wise image approximation by greedy pursuit strategies

Laura Rebollo-Neira, Ryszard MacIoł, Shabnam Bibi

Research output: Contribution to journalArticle

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 languageEnglish
Pages (from-to)1175-1178
Number of pages4
JournalIEEE Signal Processing Letters
Volume20
Issue number12
Early online date8 Oct 2013
DOIs
Publication statusPublished - 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

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