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+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html>
+<head>
+  <title>About Gamma</title>
+  <meta http-equiv="content-type"
+ content="text/html; charset=ISO-8859-1">
+</head>
+<body>
+<h2 style="text-decoration: underline; font-weight: bold;">About Gamma</h2>
+When calibrating display devices, the notion of "gamma value" quickly
+becomes a topic for discussion. Various numbers are often bandied about
+as if they have a well known and accepted meaning, but it turns out
+that gamma values are not a very precise way of specifying real world
+device behavior at all.<br>
+<br>
+A "gamma" curve is typically thought of as an ideal power curve, but no
+real world device has the necessary zero output at zero input to be
+able to match such a curve, and in general a display may not exactly
+reproduce an idealized power curve shape at all. The consequence of
+this is that there are countless ways of matching a real world curve
+with the ideal gamma power one, and each different method of matching
+will result in a different notional gamma value.<br>
+<br>
+Argyll's approximate specification and reading is simply the gamma of
+the ideal curve that matches the real 50% stimulus relative-to-white
+output level. I think this is a reasonable (robust and simple)
+approximation,
+because it matches the overall impression of brightness for an image. A
+more sophisticated approximation that could be adopted would be to
+locate the idea power curve that minimizes the total delta E of some
+collection of test values, but there are still many details that the
+final result will depend on, such as what distribution of test values
+should be used, what delta E measure should be used, and how can a
+delta E be computed if the colorimetric behavior of the device is not
+known ? Some approaches do things such as minimize the sum of the
+squares of the output value discrepancy for linearly sampled input
+values, and while this is mathematically elegant, it is hard to justify
+the choice of device space as the metric.<br>
+<br>
+There are many other ways in which it could be done, and any such
+approximation may have a quite different numerical value, even though
+the visual result is very similar. This is because the numerical power
+value is very sensitive to what's happening near zero, the very point
+that is non-ideal. Consider the sRGB curve for instance. It's
+technically composed of a power curve segment with a power of 2.4, but
+when combined with its linear segment near zero, has an overall curve
+best approximated by a power curve of gamma 2.2. Matching the 50%
+stimulus would result in yet another slightly different approximation
+value of about 2.224. All these different gamma values represent curves
+that are very visually similar.<br>
+<br>
+<img style="width: 400px; height: 400px;"
+ alt="Plot of sRGB curve vs. power of 2.224" src="srgbplot.gif"
+ align="left"><br>
+<br>
+The result of this ambiguity about what gamma values mean when applied
+to real world curves, is that it shouldn't be expected that there are
+going to be good matches between various gamma numbers, even for curves
+that are very visually similar, unless the precise method of matching
+the ideal gamma curve to the real world curve is known.<br>
+<br>
+<br>
+</body>
+</html>