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An auto-focus image system includes a focus signal generator and a pixel array coupled thereto that captures an image that includes a plurality of edges. The generator computes a focus signal from a plurality of edge-sharpness measures, each measured from and contributed by a different edge as a qua

An auto-focus image system includes a focus signal generator and a pixel array coupled thereto that captures an image that includes a plurality of edges. The generator computes a focus signal from a plurality of edge-sharpness measures, each measured from and contributed by a different edge as a quantity with a unit that is a power of a unit of length, such as a distance in the edge, an area, or an even-order central moment. A relative weight of the contribution by an edge is reduced depending on at least a pair of shape measures, each being computed from a plurality of sample-pair differences of the edge. One may be the edge-sharpness measure. The weight may be zero if the pair of shape measures falls outside a predetermined region. At least one symmetrical sequence of gradients exists such that an edge with it has reduced relative weight.

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1. A method for generating a focus signal from a plurality of edges of an image of a scene to indicate a degree of image sharpness, comprising: evaluating in a computing device a first measure and a second measure on an edge detected from the image to find a first value and a second value, respectiv

1. A method for generating a focus signal from a plurality of edges of an image of a scene to indicate a degree of image sharpness, comprising: evaluating in a computing device a first measure and a second measure on an edge detected from the image to find a first value and a second value, respectively; and,determining by use of at least the first and second values a relative extent to which the edge weighs in contributing to the focus signal as compared with other edges that contribute to the focus signal,wherein the first and second measures of any edge are each a quantity that depends on at least two image-sample differences, each image-sample difference being a difference between a pair of samples of image data, the samples being from a sequence of image data samples across said any edge,wherein the determining is not based on measuring an extent to which a sequence of gradients across the edge lacks reflection symmetry. 2. The method of claim 1, wherein the evaluating the first measure does not depend upon detection of another edge. 3. The method of claim 1, wherein a 20% decrease in an illumination of the scene does not result in a difference whether the edge is omitted or allowed to contribute to the focus signal. 4. The method of claim 1, wherein the determining determines the relative extent by comparing the first value with a predetermined criterion that depends on at least the second value. 5. The method of claim 4, further comprising: omitting or deemphasizing the edge in the generating of the focus signal where the edge does not meet the predetermined criterion. 6. The method of claim 1, wherein the determining determines the relative extent as a function of at least the first and second measures. 7. The method of claim 6, wherein the relative extent is a weight for a contribution of the edge towards the focus signal. 8. The method of claim 1, wherein any edge that contributes to the focus signal contributes an edge-sharpness measure that is a quantity computed from a plurality of samples of image data within a predetermined neighborhood of said any edge. 9. The method of claim 8, wherein the edge-sharpness measure is also the second measure. 10. The method of claim 8, wherein the edge-sharpness measure is neither the first measure nor the second measure. 11. The method of claim 10, wherein the edge-sharpness measure of said any edge is not evaluated where said any edge is omitted from the generating of the focus signal. 12. The method of claim 10, wherein the edge-sharpness measure of said any edge is a width of a predefined portion of said any edge predefined according to a predetermined manner. 13. The method of claim 10, wherein the edge-sharpness measure of said any edge is a peak gradient value of said any edge divided by a contrast across said any edge or across a predefined portion of said any edge. 14. The method of claim 10, wherein the edge-sharpness measure is a second moment of gradients in the sequence of gradients. 15. The method of claim 1, wherein the first and second measures are mutually independent in the sense that neither can be computed from the other without further involving at least one sample of image data from a predetermined neighborhood of the edge. 16. The method of claim 8, wherein the edge-sharpness measure of any edge has a unit that is a power of a unit of length, given that each sample of image data has a unit that is a unit of energy, that a difference between any pair of samples of image data divided by a distance between the samples has a unit that is a unit of energy divided by a unit of length, that a distance between gradients and a count of pixels both have a unit that is a unit of length, that a gradient value has a unit that is a unit of energy divided by a unit length, and that normalized gradient values are unitless. 17. The method of claim 1, wherein the first and second measures are both not affected by scaling the plurality of samples of image data by a non-zero scaling factor while other samples of image data are not scaled. 18. The method of claim 1, wherein the first and second measures are both affected by scaling the plurality of samples of image data by a non-zero scaling factor. 19. The method of claim 1, wherein there is a spurious sequence of gradients having perfect reflection symmetry such that the determining necessarily reduces the relative extent where the edge has the spurious sequence of gradients across itself. 20. The method of claim 19, wherein the spurious sequence of gradients is {0, 0.2, 0.2, 0.7, 0.7, 1, 0.7, 0.7, 0.2, 0.2, 0}.