OSA Incubator: Implications of Compressive Sensing Concepts to Imaging Systems
By Miaochan Zhi
Second, what is compressed sensing and imaging? One of the hosts, Mark Neifeld, University of Arizona, stated that the main motivation for compressed imaging is that images are redundant (remember the times you need to compress your pictures). Therefore it may be possible to sense sparse signals by taking far fewer measurements, hence the name compressed sensing.
In addition, traditional images based on pixels produce massive amounts of data, which leads to computational challenges. Compressed imaging, however, enables one to take much less data yet still obtain an image or signal with tolerable distortion. One of the big news of last year is the lensless camera, which is also based on compressed sensing. It uses no lens but just a single light sensitive sensor.
Finally, why a Compressive Sensing (CS) Incubator? CS can be traced back to the eighteenth century when Prony proposed an algorithm for the estimation of the parameters associated with a small number of complex exponentials sampled in the presence of noise in 1795 . Today, CS has the potential to revolutionize the sensor industry, with applications that span across commercial, defense, security and medical domains. However, while the mathematics is well understood, there is still some debate over harnessing the potential of CS for real-world applications.
For this particular Incubator, Mark, along with the other hosts Ravi Athale, Office of Naval Research; Abhijit Mahalanobis, Lockheed Martin; andJoe Mait, Army Research Laboratory are trying to answer a question– we understand the mathematics, and we understand the potential real-world applications of compressive sensing, but what is holding it back from wider-scale adoption?
This invitation only meeting has brought together an incredibly diverse group. For example, during dinner the people at my table represented academia, industry and government scientists. Stay tuned for more to come from this meeting and its participants!
Posted: 10 April 2014 by Miaochan Zhi | with 0 comments
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