This thesis describes a computational approach for analyzing the color aesthetics of images from the perspective of color theory. Our work has been informed by the works of Johannes Itten, one of the most influential theorists of color aesthetics. To the best of our knowledge, developing computational models that are based on Itten's theories is our unique contribution to Computer Vision. We focus on three aspects of color usage in visual art, namely modulation, contrast of hue and cold-warm contrast. For modulation, we introduce the color palette, a novel 3D visualization of the chromatic information of an image in the HSL space and propose a set of simple descriptors for evaluating color modulation. For contrast of hue, we assess the spatial color composition of the homogeneous regions. For cold-warm contrast, we assess the spatial color composition of the homogeneous regions and the hue adjacencies. Further, we assess the relative warmth of the homogeneous regions and adjacent hues. We also propose a visualization, namely a 3D histogram to visualize the patterns of the contrasts in an artist's paintings. We validate our methods by comparing our results with Itten's descriptions and comments. We hope that this computational approach improves the color-based features used in the aesthetic classification of images. / Graduate / 0984