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13 September 2011 Scene-based blind deconvolution image and PSF estimation
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Abstract
Most non-conventional approaches to image restoration of scenes observed over long atmospheric slant paths require multiple frames of short exposure images taken with low noise focal plane arrays. The individual pixels in these arrays often exhibit spatial non-uniformity in their response. In addition base motion jitter in the observing platform introduces a frame-to-frame linear shift that must be compensated for in order for the multi-frame restoration to be successful. In this paper we describe a maximum aposteriori parameter estimation approach to the simultaneous estimation of the frame-to-frame shifts and the array non-uniformity. This approach can be incorporated into an iterative algorithm and implemented in real time as the image data is being collected. We can not only estimate the scene, but also the angle dependent point spread function. We present a brief derivation of the algorithm as well as its application to actual image data collected from an airborne platform.
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David C. Dayton, John D. Gonglewski, and Michael Myers "Scene-based blind deconvolution image and PSF estimation", Proc. SPIE 8165, Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems, 81650N (13 September 2011); https://doi.org/10.1117/12.896556
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