Computer Science – Multimedia
Scientific paper
2012-03-26
Computer Science
Multimedia
Submitted to IEEE Transactions on Image Processing
Scientific paper
Numerous applications in signal processing have benefited from the theory of compressed sensing which shows that it is possible to reconstruct signals sampled below the Nyquist rate when certain conditions are satisfied. One of these conditions is that there exists a known transform that represents the signal with a sufficiently small number of non-zero coefficients. However when the signal to be reconstructed is composed of moving images or volumes, it is challenging to form such regularization constraints with traditional transforms such as wavelets. In this paper, we present a motion compensating prior for such signals that is derived directly from the optical flow constraint and can utilize the motion information during compressed sensing reconstruction. Proposed regularization method can be used in a wide variety of applications involving compressed sensing and images or volumes of moving and deforming objects. It is also shown that it is possible to estimate the signal and the motion jointly or separately. Practical examples from magnetic resonance imaging has been presented to demonstrate the benefit of the proposed method.
Bilen Cagdas
Selesnick Ivan
Wang Yao
No associations
LandOfFree
Compressed Sensing for Moving Imagery in Medical Imaging does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Compressed Sensing for Moving Imagery in Medical Imaging, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Compressed Sensing for Moving Imagery in Medical Imaging will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-642645