1. A method of reducing wrap-around in a digital image processing process that compares a digital test image and a digital reference image and that includes one or more convolution steps, the method comprising: a) producing a reference luminance image from the reference image and a test luminance image from the test image; b) producing a local mean luminance reference image as a convolution of the reference luminance image and a luminance filter function; c) producing a test contrast image that is at least one of the following: (c 1 ) a mathematical combination of the test luminance image and the local mean luminance reference image and (c 2 ) a mathematical combination of the test luminance image, the local mean luminance reference image and a border aperture function and (c 3 ) a mathematical combination of the test luminance image, the local mean luminance reference image and an image of a border surrounding the reference image; d) producing a reference contrast image that is at least one of the following: (d 1 ) a mathematical combination of the reference luminance image and the local mean luminance reference image and (d 2 ) a mathematical combination of the reference luminance image, the local mean luminance reference image and the border aperture function; e) applying a contrast sensitivity filter to the test contrast image to produce a filtered test image; f) applying the contrast sensitivity filter to the reference contrast image to produce a filtered reference image; g) providing a difference image by at least one of the following two processes: (g 1 ) subtracting the filtered reference image from the filtered test image to produce a difference image, and (g 2 ) producing a mask image as a mathematical combination of the filtered reference image with a masking filter, and producing a difference image as a ratio of the difference image and the mask image; h) producing a just noticeable difference image as a mathematical combination of the difference image with a window function; and i) pooling the just noticeable difference image to produce a visibility metric, wherein the convolution operation in at least one of process (b) and process (h) is performed using a confined convolution process that comprises: (i-1) receiving an image I(x,y), expressed as an array of k xo -by-k y0 pixels in an x-direction and in a y-direction, respectively, where k x0 and k y0 are selected positive integers; (i-2) padding the image I(x,y) with k x zeroes in the x-direction and by k y zeroes in the y-direction, to provide a first intermediate image I 1 (x,y), expressed as an array of (k x0 +k x )-by-(k y0 +k y ) pixels in the x-direction and in the y-direction, respectively, where k x and k y are selected non-negative integers; (i-3) convolving the first intermediate image I 1 (x,y) with a selected non-negative kernel function K(x,y), expressed as an array of k x -by-k y pixels in the x-direction and in the y-direction, respectively;, to obtain a second intermediate image I 2 (x,y) expressed as an array of (k x0 +k x )-by-(k y0 +k y ) pixels in the x-direction and in the y-direction, respectively; and (i-4) cropping the second intermediate image I 2 (x,y) to an array of k x0 -by-k y0 pixels in the x-direction and in the y-direction, respectively, to obtain a third intermediate image I 3 (x,y), expressed as an array of k x0 -by-k y0 pixels in the x-direction and in the y-direction, respectively.