Wide-area image restoration using a new iterative registration method

Donald Fraser; Andrew J. Lambert

doi:10.1117/12.409287

16 November 2000 Wide-area image restoration using a new iterative registration method

Donald Fraser, Andrew J. Lambert

Proceedings Volume 4123, Image Reconstruction from Incomplete Data; (2000) https://doi.org/10.1117/12.409287
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Over a wide field of view (e.g., 100 arcsec in optical astronomy) the point spread function due to atmospheric effects is found to be far form position invariant, and appears as a combination of local warping and local blurring. Recently, we discussed a method in which the first step in restoration is to register all points in every frame of a movie sequence to the corresponding points in a prototype image. After registration, each frame is de- warped and summed to form an average, motion-blur corrected result. Previously, we applied a hierarchical, windowed cross correlation process to obtain local x and y registration information, similar to common methods in stereo cartography. We discuss a new approach to image registration for this purpose. Suppose two images to be registered differ mainly in varying random, but spatially coherent warping (such as occurs as one effect of a slowly varying wavefront tip-tilt over a wide field of vies). Imagine that one image, the reference image, is represented by a solid surface corresponding to its intensity distribution. Imagine that the second image is also represented by a surface, but in the form of a flexible, rubber mold. If the two images are identical, then the mold fits the solid like a glove. If one image includes local warping relative to the other, then the mold or glove must be forced to fit though local distortions.

Citation Download Citation

Donald Fraser and Andrew J. Lambert "Wide-area image restoration using a new iterative registration method", Proc. SPIE 4123, Image Reconstruction from Incomplete Data, (16 November 2000); https://doi.org/10.1117/12.409287

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