Fast search for best representations in multitree dictionaries.
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.
Huang
Yan
Y
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. yanh.huang@gmail.com
Pollak
Ilya
I
Do
Minh N
MN
Bouman
Charles A
CA
D000465:Algorithms; D003196:Computer Graphics; D044962:Data Compression / Q000379:methods*; D003661:Decision Support Techniques; D004014:Dictionaries as Topic; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009716:Numerical Analysis, Computer-Assisted; D012815:Signal Processing, Computer-Assisted