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    <p>I don't know about opencv.</p> <p>If I were trying to get an approximate measurement of where an imagine is on the sharp-to-blurry spectrum, I'd start from the observation that the sharpness of parts of an image is evident from the contrast between adjacent pixels - something like <code>max(c1 * abs(r1 - r2), c2 * abs(g1 - g2), c3 * abs(b1 - b2))</code> where c1-3 weigh perceptual importance of each of the red, green and blue channels, and the two pixels are (r1,g1,b1) and (r2,g2,b2)).</p> <p>Many tweaks possible, such as raising each colour's contribution to a power to emphasise changes at the dark (power &lt;1)or bright (power >1) end of the brightness scale. Note that the <code>max()</code> approach considers sharpness for each colour channel separately: a change from say (255,255,255) to (0,255,255) is very dramatic despite only one channel changing.</p> <p>You may find it better to convert from RBG to another colour representation, such as Hue/Saturation/Value (there'll be lots of sites online explaining the HSV space, and formulas for conversions).</p> <p>Photographically, we're usually interested in knowing that the in-focus part of the image is sharp (foreground/background blur/bokeh due to shallow depth of field is a normal and frequently desirable quality) - the clearest indication of that is high contrast in some part of the image, suggesting you want the maximum value of adjacent-pixel contrasts. That said, some focused pixtures can still have very low local contrasts (e.g. a picture of a solid coloured surface). Further, damaged pixel elements on the sensor, dirt on the lens/sensor, and high-ISO / long-exposure noise may all manifest as spots of extremely high contrast. So the validity of your result's always going to be questionable, but it might be ball-park right a useful percentage of the time.</p>
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