In this paper, we propose an algorithm for the measure of local and global contrast in digital images. It applies locally, at various sub-sampled levels, a simplified computation of local contrast based on DOG and finally it recombines all the values to obtain a global measure. The proposed method comes from the modification of a previous algorithm with a different local measure of contrast and with a parameterized way to recombine color channels. As new approach we propose the idea of recombining the channels following measures taken from the image itself. Preliminary tests and results are presented and discussed. Introduction Since the first studies on contrast in images, it has emerged how arduous it could be to give a definition of contrast and, moreover, how subjective and related to the observation task or observer experience this definition could turn out to be. For this reason, the first approaches to this topic have confined themselves to study the phenomenon from rather limited points of view, operating in controlled situations and under very restrictive conditions, the so-called "void conditions". After this very first experiments more complex measures have been devised, but a measure of contrast in images is still not clearly
['Alessandro Rizzi', 'Gabriele Simone', 'Roberto Cordone']
A Modified Algorithm for Perceived Contrast Measure in Digital Images