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Information theory is used to formulate a single figure of merit for assessing the performance of line-scan imaging systems as a function of their spatial response (PSF or MTF), sensitivity, and sampling and quantization intervals and of the statistical properties of a random radiance field. Information density and efficiency (i.e., the ratio of information density to data density) tend to be optimum when the MTF and sampling passband of the imaging system are matched to the Wiener spectrum of the radiance field. Computational results for the statistical properties of natural radiance fields and the responses of common line-scan imaging mechanisms indicate that information density and efficiency are not strongly sensitive to variations in typical statistical properties of the radiance field and that the best practically realizable performance is approached when the sampling intervals are ~0.5-0.7 times the equivalent diameter of the PSF.
Huck et al. (Mon,) studied this question.