Hierarchized block wise image approximation by greedy pursuit strategies

TL;DR

This paper introduces a hierarchical greedy pursuit strategy for block-wise image approximation, optimizing the selection process to efficiently approximate image partitions, especially on transformed images.

Contribution

It presents a novel hierarchical greedy approach for block-wise image approximation, improving efficiency in approximating image partitions on transformed images.

Findings

Effective approximation of image partitions demonstrated

Hierarchized greedy pursuit improves approximation efficiency

Applicable to transformed image partitions

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.