Paper
25 November 1985 Use Of Matched Filtering To Identify Speckle Locations.
E. Ribak, E. K. Hege, J. C. Christou
Author Affiliations +
Abstract
In many cases the speckle maxima required for the our realization of the Shift-and-Add method are not well defined. This is due mainly to Poisson noise, inherent in the detection process, which obliterates the shape of faint speckles. The problem is aggravated for extended objects with local peaks, such as binary stars. As a remedy, we use a filter that smoothes out each speckle and at the same time defines its location. The best filter should be very close to the mean speckle itself: a matched filter. The initial guess for this filter is a bell function, slightly wider than the expected mean speckle. This initial guess is used to locate filtered speckle maxima which are then used to produce a better mean speckle estimate by shift-and add. The procedure is iterated until the mean speckle converges. We find that the iterative speckle estimate is not the optimum matched filter. The most suitable filter must suppress the variable background created by coalescing speckles in a large speckle cloud as well as smooth the single-photon event noise. Thus we combine the mean speckle with a band-pass filter into a matched filter. Local speckle maxima are thus enhanced, whereas single photons are discriminated against by using a comparison low-pass filtered frame, since they do not contain much power. The combined process, speckle identification and weighted-shift-and-add, can be carried out in the image plane or in the Fourier plane. We have experimented in both domains.
© (1985) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
E. Ribak, E. K. Hege, and J. C. Christou "Use Of Matched Filtering To Identify Speckle Locations.", Proc. SPIE 0556, Intl Conf on Speckle, (25 November 1985); https://doi.org/10.1117/12.949540
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Cited by 3 scholarly publications.
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KEYWORDS
Speckle

Optical filters

Telescopes

Linear filtering

Bandpass filters

Apodization

Electronic filtering

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