Modulation-transfer-function analysis for sampled image systems
Stephen K. Park, Robert A. Schowengerdt, Mary-Anne Kaczynski
Abstract
Stephen K. Park, Robert A. Schowengerdt, Mary-Anne Kaczynski
Abstract
Sampling generally causes the response of a digital imaging system to be locally shift-variant and not directly amenable to MTF analysis. However, this paper demonstrates that a meaningful system response can be calculated by averaging over an ensemble of point-source system inputs to yield an MTF which accounts for the combined effects of image formation, sampling, and image reconstruction. As an illustration, the MTF of the Landsat MSS system is analyzed to reveal an average effective IFOV which is significantly larger than the commonly accepted value, particularly in the along-track direction where undersampling contributes markedly to an MTF reduction and resultant increase in image blur.
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Sampling generally causes the response of a digital imaging system to be locally shift-variant and not directly amenable to MTF analysis. However, this paper demonstrates that a meaningful system response can be calculated by averaging over an ensemble of point-source system inputs to yield an MTF which accounts for the combined effects of image formation, sampling, and image reconstruction. As an illustration, the MTF of the Landsat MSS system is analyzed to reveal an average effective IFOV which is significantly larger than the commonly accepted value, particularly in the along-track direction where undersampling contributes markedly to an MTF reduction and resultant increase in image blur.
Key concepts: Undersampling, Optical transfer function, Point spread function, Optics, Nyquist frequency, Image quality, Image restoration, Sampling (signal processing)