Hierarchized block wise image approximation by greedy pursuit strategies
This work addresses image compression or processing challenges, but it appears incremental as it builds on existing greedy pursuit methods for partitioned images.
The paper tackles the problem of approximating images partitioned into blocks using greedy selection strategies, achieving a method that selects elements for each block and determines a hierarchical sequence for block approximation to meet global sparsity requirements.
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.