Scene-based blind deconvolution in the presence of anisoplanatism

David C. Dayton; John D. Gonglewski; Chad St. Arnauld

doi:10.1117/12.828504

11 August 2009 Scene-based blind deconvolution in the presence of anisoplanatism

David C. Dayton, John D. Gonglewski, Chad St. Arnauld

Proceedings Volume 7466, Advanced Wavefront Control: Methods, Devices, and Applications VII; 74660K (2009) https://doi.org/10.1117/12.828504
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Most non-conventional approaches to image restoration of objects observed over long atmospheric paths require multiple frames of short exposure images taken with low noise focal plane arrays. Multi-frame blind deconvolution is such an approach. In most cases the object is assumed to extend only over a single isoplanatic patch. However, when one is observing scenes over a near horizontal slant path the isoplantic patch size is small due to extended atmospheric turbulence over the entire slant path, and the scene usually extends over many isoplanatic patches. 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 a-posteriori parameter estimation approach to the simultaneous estimation of the frame-to-frame shifts and non-isoplanatic point spread functions. This approach can be incorporated into an iterative algorithm. We present a brief derivation of the algorithm as well as its application to actual image data collected from airborne and ground based platforms.

Citation Download Citation

David C. Dayton, John D. Gonglewski, and Chad St. Arnauld "Scene-based blind deconvolution in the presence of anisoplanatism", Proc. SPIE 7466, Advanced Wavefront Control: Methods, Devices, and Applications VII, 74660K (11 August 2009); https://doi.org/10.1117/12.828504

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KEYWORDS

Deconvolution

Algorithm development

Detection and tracking algorithms

Image processing

Detector arrays

Point spread functions

Airborne remote sensing

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