Fast $M$ -Term Pursuit for Sparse Image Representation

This letter introduces a practical algorithm called fast -term pursuit (FMTP) for sparse approximation in redundant dictionaries. As an extension of the popular matching pursuit (MP), FMTP presents a good trade-off between high approximation performance and efficient implementation. Based on the effective estimation of the incoherence among dictionary atoms, FMTP combines the strength of both sequential and parallel techniques. Experimental results show that with slight approximation losses, FMTP yields significant speed improvements over the latest fast algorithms. It achieves a speedup of 63.46 in comparison with the MP approach.