Paper
13 September 2011 Scene-based blind deconvolution image and PSF estimation
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Point spread functions

Algorithm development

Detection and tracking algorithms

Deconvolution

Image processing

Detector arrays

Image analysis

Back to Top