A perceptually based spectral model for isotropic textures

Color is routinely used to visualize interval and ordinal data, while texture is not. For color, a variety of perceptually based models is available, which can be used to convey data via straightforward mapping. The dimensionality of texture is less well understood and there are almost no perceptually based and validated models available to generate textures on demand. We present a perceptually based texture synthesis model for isotropic textures. The model uses additive synthesis of band-limited noise in the spectral domain, comparable to the RGB (red, green, blue) model for color. Via user experiments, we have derived a three-dimensional model to control the amplitudes per band in a perceptually intuitive way, comparable to the HSV (hue, saturation, value) model for color. The three dimensions used are contrast, spatial frequency, and spectral purity. Besides a mapping to the amplitudes, we have derived a mapping to a perceptually equidistant space. We show how such textures can be combined with color; applications are presented.