4 September 1979 Digital image multiple-frame restoration through atmospheric and instrumental noises
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Proceedings Volume 0186, Digital Processing of Aerial Images; (1979) https://doi.org/10.1117/12.957510
Event: 1979 Huntsville Technical Symposium, 1979, Huntsville, United States
Abstract
Improved object data has been extracted from multiple frames of poor quality imagery. The individual images had been degraded by propagation through atmospheric turbulence or water waves, and then mixed with instrumental noises. Using knowledge of the image formation and degradation process, Gregory's technique for "moments of good seeing" used in optical astronomy was implemented with digital processing. Digital implementation allowed the techniques to be applied locally to isoplanatic regions for those cases with nonuniform and nonstationary random media. The statistically correct location of the object was assumed to be determined by the long term average of the image. After proper registration a Kalman filter, adapted for correlated disturbances, was used to sharpen the mean-square spread of gray levels for each pixel with respect to multiple frames. An enhancement factor Anâœ"n for signal to noise ratio was obtained by uniformly averaging n-correlated disturbances. The best that one could do for purely random noise was a uniformly weighted average, and a recursively weighted average can not be any worse than a uniformly weighted one. Laboratory simulation of underwater objects and field data with atmospheric degradation has successfully illustrated the proposed method of digital image multiple-frame restoration, i.e. local implementation of "moments of good seeing" and Kalman filtering for correlated distrubances.
© (1979) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hwaling Harold Szu, Hwaling Harold Szu, J. S. Lee, J. S. Lee, J. A. Blodgett, J. A. Blodgett, } "Digital image multiple-frame restoration through atmospheric and instrumental noises", Proc. SPIE 0186, Digital Processing of Aerial Images, (4 September 1979); doi: 10.1117/12.957510; https://doi.org/10.1117/12.957510
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