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15 April 2008 What causes sampling artifacts?
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The sampling process creates an infinite number of new frequencies that were not present in the original scene. For an under-sampled system (which is characteristic of nearly all imaging systems), the replicated frequencies can overlap scene frequencies. An optical anti-alias filter can eliminate the overlapping but does not prevent frequency replication. Frequencies above the Nyquist frequency are eliminated by an ideal reconstruction filter. As overlapping increases or with less than ideal reconstruction, the resultant image is distorted. The phases associated with the replicated frequencies violate linear-shift-invariant system requirements. As a result, movement of the scene with respect to the detector array creates ambiguity in edge locations further distorting imagery. While sampling theory suggests that sharp cutoff filters are required, these filters will create ringing (Gibbs phenomenon) in the image. Replicated spectra that appear in the image are called the spurious response. Out-of-band spurious response (above Nyquist frequency) looks very similar to the input but with phase variation. The phase errors interfere with target recognition and identification. In-band spurious response (frequencies less than the Nyquist frequency) appears somewhat like noise. At this juncture it is not clear how this "noise" interferes with recognition and identification tasks. It may only affect detection. Since the sampling process replicates frequencies, it is possible to extract information with reconstruction band-pass filters whose center frequency is above the Nyquist frequency.
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Gerald C. Holst "What causes sampling artifacts?", Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 694102 (15 April 2008);

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