@inproceedings{3cc0c52a183c49fba04bc4975ba39095,
title = "Compressive imaging of color images",
abstract = "In this paper, we propose a novel compressive imaging framework for color images. We first introduce an imaging architecture based on combining the existing single-pixel Compressive Sensing (CS) camera with a Bayer color filter, thereby enabling acquisition of compressive color measurements. Then we propose a novel CS reconstruction algorithm that employs joint sparsity models in simultaneously recovering the R, G, B channels from the compressive measurements. Experiments simulating the imaging and reconstruction procedures demonstrate the feasibility of the proposed idea and the superior quality in reconstruction.",
keywords = "Bayer color filter, Compressive sensing, Joint sparsity models, l -minimization",
author = "Pradeep Nagesh and Baoxin Li",
year = "2009",
doi = "10.1109/ICASSP.2009.4959820",
language = "English (US)",
isbn = "9781424423545",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "1261--1264",
booktitle = "2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009",
note = "2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 ; Conference date: 19-04-2009 Through 24-04-2009",
}