Open Access Open Access  Restricted Access Subscription or Fee Access

Sparse Image Reconstruction Using Improved Regularized Orthogonal Matching Pursuit

Meenakshi, Sumit Budhiraja


Compressive Sensing (CS) utilizes the sparsity of images to reduce the number of measurements and is able to achieve reduction in amount of storage required; breaking the limitations of Nyquist Shannon theorem. CS based image reconstruction is capable of providing easy and accurate sparse reconstruction; though with longer running time. Regularised Orthogonal Matching Pursuit (ROMP) is one of the greedy algorithms which enable faster implementation of image recovery, but the performance of recovery is not satisfactory. In this paper, improved ROMP method is presented which works on low frequency coefficients of the image under certain stopping conditions; thus saving memory with reduced running time. The recovery process is followed by thresholding; so that significant elements are identified and smaller components are rejected. The simulation results for both noiseless and noisy cases show that this method provides better PSNR and faster means for sparse recovery from inaccurate and fewer measurements.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.