TY - GEN
T1 - Compressive sampling vs. conventional imaging
AU - Haupt, Jarvis
AU - Nowak, Robert
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Compressive sampling (CS), or "Compressed Sensing," has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively small number of non-traditional samples in the form of randomized projections that are capable of capturing the most salient information in an image. If the image being sampled is compressible in a certain basis (e.g., wavelet), then under noiseless conditions the image can be much more accurately recovered from random projections than from pixel samples. However, the performance of CS can degrade markedly in the presence of noise. In this paper, we compare CS to conventional imaging by considering a canonical class of piecewise smooth image models. Our conclusion is that CS can be advantageous in noisy imaging problems if the underlying image is highly compressible or if the SNR is sufficiently large.
AB - Compressive sampling (CS), or "Compressed Sensing," has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively small number of non-traditional samples in the form of randomized projections that are capable of capturing the most salient information in an image. If the image being sampled is compressible in a certain basis (e.g., wavelet), then under noiseless conditions the image can be much more accurately recovered from random projections than from pixel samples. However, the performance of CS can degrade markedly in the presence of noise. In this paper, we compare CS to conventional imaging by considering a canonical class of piecewise smooth image models. Our conclusion is that CS can be advantageous in noisy imaging problems if the underlying image is highly compressible or if the SNR is sufficiently large.
KW - Image sampling
KW - Random projections
UR - http://www.scopus.com/inward/record.url?scp=78649846510&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649846510&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2006.312576
DO - 10.1109/ICIP.2006.312576
M3 - Conference contribution
AN - SCOPUS:78649846510
SN - 1424404819
SN - 9781424404810
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1269
EP - 1272
BT - 2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
T2 - 2006 IEEE International Conference on Image Processing, ICIP 2006
Y2 - 8 October 2006 through 11 October 2006
ER -