ENH: adding a recipe for contrast enhancement application

Documentation/Cookbook/rst/recipes/contrast_enhancement.rst

+Visual product and contrast enhancement
+========================================================
+Sensor images have often a wide dynamic range. Whereas it is very helpful
+to have high precision to do complex processing, it is pretty hard to display
+wide range of dynamic, even on modern screen. The dynamic range for basic
+screen is of 8 bits. Data can contain 12 or 16 bits (or even more!).
+The contrast enhancement application is aiming at reducing this dynamic
+by compressing it in a smarter way than just linear compression.
+In a linear compression, compression changes the dynamic range (for instance
+from 12 to 8 bits) but does not change the repartition of the pixel.
+//math here
+Here the equalization of histogram is creating a look up table in order to
+maximize the use of dynamics.
+//math here
+With this in mind you can then try it on your own images with the simple
+following use :
+//Syntax here
+
+Advanced parameters
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+You can see that more parameter are available in the application. Let us see
+what there are for.
+First what you want to equalize. There is two modes :
+* luminance : you provide the application with a 3 bands image and the
+equalization will be done on a single band which will be a composition of
+the original bands. The computed gain will then be applied on the different
+bands. The classical use of this method is to conserve ratio between the
+different color, conserve the hue.
+* channel : you provide the application with a n bands image and each of
+them are equalized independently.
+//syntax here?
+The other main mode is the local equalization. You can choose a window
+size that will be use to split the image in tiles and histograms will be
+computed over those tiles. Gain will be interpolated between the adjacent
+tiles in order to give a smooth result.
+
+The application also offers a way to limit contrast by adjusting original
+histogram. The limitation factor represent the limit height that can have
+any bucket of the histogram : we compute the height of the perfect flat
+histogram and the maximal height is the limitation factor time this "flat
+height".
+//image here
+
+Finally you have the choice to ignore a particular value with the nodata
+parameter, and also the choice to put manually your minimum and maximum value.
+Any value out of bound will be ignored.
+