Statistically Driven Sparse Image Approximation

Rosa M. Figueras i Ventura, Eero P. Simoncelli
2007 Proceedings of IEEE international conference on image processing  
Finding the sparsest approximation of an image as a sum of basis functions drawn from a redundant dictionary is an NPhard problem. In the case of a dictionary whose elements form an overcomplete basis, a recently developed method, based on alternating thresholding and projection operations, provides an appealing approximate solution. When applied to images, this method produces sparser results and requires less computation than current alternative methods. Motivated by recent developments in
more » ... tistical image modeling, we develop an enhancement of this method based on a locally adaptive threshold operation, and demonstrate that the enhanced algorithm is capable of finding sparser approximations with a decrease in computational complexity.
doi:10.1109/icip.2007.4378991 dblp:conf/icip/VenturaS07 fatcat:e2o3yujdpranpe46ajbfwokwqu