Maximum a posteriori estimation of Markov random fields (MRFs) is a popular research area in computer vision, and many algorithms have been proposed to deal with these types of problems. The phase-unwrapping problem is modeled as the optimization of MRFs in this research, and the binary algorithm, improved quadratic pseudo-Boolean optimization, is utilized to solve the phase-unwrapping problem. Both the interferometric phases generated from the commonly used computer simulated surfaces and also real terrains are researched in the experimental section, and the unwrapping results are compared. The proposed algorithm achieves unwrapping results comparable to the state-of-the-art unwrapping method but costs less time for large-scale phase images.