Imaging via Compressive Sampling Export

@article{Romberg08, abstract = {Image compression algorithms convert high-resolution images into a relatively small bit streams in effect turning a large digital data set into a substantially smaller one. This article introduces compressive sampling and recovery using convex programming.}, author = {Romberg, J.}, booktitle = {Signal Processing Magazine, IEEE}, citeulike-article-id = {2891151}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/MSP.2007.914729}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4472239}, day = {21}, doi = {10.1109/MSP.2007.914729}, journal = {Signal Processing Magazine, IEEE}, keywords = {cs, mri}, month = {March}, number = {2}, pages = {14--20}, posted-at = {2009-10-26 16:24:31}, priority = {0}, title = {Imaging via Compressive Sampling}, url = {http://dx.doi.org/10.1109/MSP.2007.914729}, volume = {25}, year = {2008} }

TY - JOUR ID - Romberg08 L3 - citeulike-article-id:2891151 N2 - Image compression algorithms convert high-resolution images into a relatively small bit streams in effect turning a large digital data set into a substantially smaller one. This article introduces compressive sampling and recovery using convex programming. IS - 2 JF - Signal Processing Magazine, IEEE EP - 20 TI - Imaging via Compressive Sampling VL - 25 T2 - Signal Processing Magazine, IEEE SP - 14 KW - cs KW - mri AU - Romberg, J PY - 2008/03/21/ UR - http://dx.doi.org/10.1109/MSP.2007.914729 ER -