Title :
Iterative multiframe super-resolution algorithms for atmospheric turbulence-degraded imagery
Author :
Sheppard, David G. ; Hunt, Bobby R. ; Marcellin, Michael W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
Abstract :
Algorithms for image recovery with super-resolution from sequences of short-exposure images are presented. Both deconvolution from wavefront sensing (DWFS) and blind deconvolution are explored. A multiframe algorithm is presented for DWFS which is based on maximum a posteriori (MAP) formulation. A multiframe blind deconvolution algorithm is presented based on a maximum likelihood formulation with strict constraints incorporated using nonlinear reparameterizations. Quantitative simulation of imaging through atmospheric turbulence and wavefront sensing are used to demonstrate the super-resolution performance of the algorithms
Keywords :
Bayes methods; atmospheric turbulence; deconvolution; image resolution; image restoration; image sequences; iterative methods; maximum likelihood estimation; stochastic processes; Bayes maximum likelihood criteria; MAP; Poisson data; atmospheric turbulence; atmospheric turbulence-degraded imagery; blind deconvolution; constraints; image recovery algorithms; image restoration; imaging; iterative multiframe super-resolution algorithms; maximum a posteriori formulation; multiframe blind deconvolution algorithm; nonlinear reparameterizations; quantitative simulation; short-exposure image sequences; wavefront sensing; Atmospheric waves; Deconvolution; Degradation; Equations; Image resolution; Iterative algorithms; Nonlinear optics; Optical attenuators; Optical sensors; Spatial resolution;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.678121
