Comparison of restoration algorithms on high-altitude infrared images

Computer Science – Performance

Scientific paper

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Scientific paper

Image restoration techniques, iterative and non-iterative, are applied to high-speed infrared images from a ground based telescope of objects at altitudes to reduce the degradation of the images caused by atmospheric turbulence, vibration, and systematic aberrations. Comparisons are made among the following: The Wiener filter, the Richardson-Lucy method, the CLEAN algorithm, and the maximum entropy method. The Wiener and Richardson-Lucy filters are found to have the best overall performance and flexibility when the PSF is known. The Wiener filter consistently provides the shortest restoration time for each set of test images. A good estimate of the PSF, obtained using Tatians's method, is used as an input parameter for each of the restoration algorithms.

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