Fast search for best representations in multitree dictionaries

  • Authors:
  • Yan Huang;I. Pollak;M. N. Do;C. A. Bouman

  • Affiliations:
  • Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA;-;-;-

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 2006

Quantified Score

Hi-index 0.01

Visualization

Abstract

We address the best basis problem - or, more generally, the best representation problem: Given a signal, a dictionary of representations, and an additive cost function, the aim is to select the representation from the dictionary which minimizes the cost for the given signal. We develop a new framework of multitree dictionaries, which includes some previously proposed dictionaries as special cases. We show how to efficiently find the best representation in a multitree dictionary using a recursive tree-pruning algorithm. We illustrate our framework through several examples, including a novel block image coder, which significantly outperforms both the standard JPEG and quadtree-based methods and is comparable to embedded coders such as JPEG2000 and SPIHT.