Distributed Acquisition and Image Super-Resolution Based on Continuous Moments from Samples

Recently, new sampling schemes were presented for signals with finite rate of innovation (FRI) using sampling kernels reproducing polynomials or exponentials. In this paper, we extend those sampling schemes to a distributed acquisition architecture in which numerous and randomly located sensors are pointing to the same area of interest. We emphasize the importance played by moments and show how to acquire efficiently FRI signals with a set of sensors. More importantly, we also show that those sampling schemes can be used for accurate registration of affine transformed and low-resolution images. Based on this, a new super-resolution a


Published in:
2006 International Conference on Image Processing, 3309-3312
Presented at:
2006 International Conference on Image Processing, Atlanta Marriott Marquis, Atlanta, GA, USA, 8-11 October 2006
Year:
2006
Publisher:
IEEE
Keywords:
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 Record created 2012-10-25, last modified 2018-09-13

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