Statistics – Applications
Scientific paper
Dec 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001spie.4490..282j&link_type=abstract
Proc. SPIE Vol. 4490, p. 282-289, Multifrequency Electronic/Photonic Devices and Systems for Dual-Use Applications, Andrew R. Pi
Statistics
Applications
Scientific paper
How to obtain sharp images when viewing through a turbid medium is a problem that arises in a number of applications, including optical biomedical imaging and optical surveillance in the presence of clouds. The main problem with this type of imagery is that it is difficult to accurately characterize the turbid medium sufficiently well to generate a point spread function that can be used to deconvolve the blurred data (and thus increase the resolution). We discuss the use of blind deconvolution as a means of estimating both the blur-free target and the system point spread function. We compare restorations obtained using a non-linear blind deconvolution algorithm with those obtained using a linear backpropagation algorithm. Preliminary results indicate that the blind deconvolution algorithm produces the more visually pleasing restorations. Moreover, it does so without requiring any prior knowledge of the characteristics of the turbid medium, or of what the blur-free target should look like: an important advance over the backpropagation algorithm.
Hege Keith E.
Jefferies Stuart M.
Matson Charles L.
Schulze Kathy J.
Stoltenberg Kurt
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