A technique to estimate the radial dependence of the noise power spectrum of images is proposed in which the calculations are conducted solely in the spatial domain of the noise image. The noise power spectrum averaged over a radial spatial-frequency interval is obtained from the variance of a noise image that has been convolved with a small kernel that approximates a Laplacian operator. Recursive consolidation of the image by factors of two in each dimension yields estimates of the noise power spectrum over that full range of spatial frequencies.
Keywords: noise power spectrum, Wiener spectrum, granularity, pass-band granularity, Laplacian, binomial kernels, Gaussian pyramid, Laplacian pyramid
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