1. A computer-implemented method of classifying an image, comprising: applying a view-based classifier to an image, wherein the classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of the plurality of sub-classifiers, the log-likelihood ratio including a ratio of two graphical probability models, a graphical probability model including a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables.