Image histograms capture the way a scene is rendered using the available pixel intensity values. By analyzing the distribution of the pixel values over an image, it is possible to use this information to modify and possibly improve an image. This recipe explains how we can use a simple mapping function, represented by a look-up table, to modify the pixel values of an image. As we will see, look-up tables are often produced from histogram distributions.
A look-up table is a simple one-to-one (or many-to-one) function that defines how pixel values are transformed into new values. It is a 1D array with, in the case of regular gray-level images, 256 entries. Entry i of the table gives you the new intensity value of the corresponding gray level, which is expressed as follows:
newIntensity= lookup[oldIntensity];
The cv::LUT function in OpenCV applies a look-up table to an image in order to produce a new image. Since...