Markov Random Fields for Vision and Image Processing

This volume demonstrates the power of the Markov random field (MRF) invision, treating the MRF both as a tool for modeling image data and, utilizingrecently developed algorithms, as a means of making inferences about images. Theseinferences concern underlying image and scene structure as well as solutions to suchproblems as image reconstruction, image segmentation, 3D vision, and objectlabeling. It offers key findings and state-of-the-art research on both algorithmsand applications. After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs;presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods;discusses advanced algorithmic topics; addresses limitations of the strong localityassumptions in the MRFs discussed in earlier chapters; and showcases applicationsthat use MRFs in more complex ways, as components in bigger systems or withmultiterm energy functions. The book will be an essential guide to current researchon these powerful mathematical tools.