This paper reviews recent best basis search algorithms. The problem under consideration is to select a representation from a dictionary which minimizes an additive cost function for a given signal. We describe a new framework of multitree dictionaries, and an efficient algorithm for finding the best representation in a multitree dictionary. We illustrate the algorithm through image compression examples.
We propose new best basis search algorithms for local cosine dictionaries. We provide several algorithms for dictionaries of various complexity. Our framework generalizes the classical best local cosine basis selection based on a dyadic tree.