HISTOGRAM CONTRAST ANALYSIS AND THE VISUAL SEGREGATION OF IID TEXTURES

A new psychophysical methodology is introduced, histogram contrast ana lysis, that allows one to measure stimulus transformations, f, used by the visual system to draw distinctions between different image region s. The method involves the discrimination of images constructed by sel ecting texture micropatterns randomly and independently (across locati ons) on the basis of a given micropattern histogram. Different compone nts of f are measured by use of different component functions to modul ate the micropattern histogram until the resulting textures are discri minable. When no discrimination threshold can be obtained for a given modulating component function, a second titration technique may be use d to measure the contribution of that component to f. The method inclu des several strong tests of its own assumptions. An example is given o f the method applied to visual textures composed of small, uniform squ ares with randomly chosen gray levels. In particular, for a fixed mean gray level mu and a fixed gray-level variance sigma2, histogram contr ast analysis is used to establish that the class S of all textures com posed of small squares with jointly independent, identically distribut ed gray levels with mean mu and variance sigma2 is perceptually elemen tary in the following sense: there exists a single, real-valued functi on f(S) of gray level, such that two textures I and J in S are discrim inable only if the average value of f(S) applied to the gray levels in I is significantly different from the average value of f(S) applied t o the gray levels in J. Finally, histogram contrast analysis is used t o obtain a seventh-order polynomial approximation of f(S).