Applications
Matching pursuit has been applied to signal, image and video coding, shape representation and recognition, 3D objects coding, and in interdisciplinary applications like structural health monitoring. It has been shown that it performs better than DCT based coding for low bit rates in both efficiency of coding and quality of image. The main problem with Matching Pursuit is the computational complexity of the encoder. In the basic version of an algorithm the large dictionary has to be searched at each iteration. Improvements include the use of approximate dictionary representations and suboptimal ways of choosing the best match at each iteration (atom extraction).
The Matching Pursuit algorithm is also used in dictionary learning. In this algorithm, atoms are learned from a database and not chosen among generic dictionaries.
Read more about this topic: Matching Pursuit