Multifrequency absolute phase estimation via graph cuts

Many imaging systems, e.g., interferometric synthetic aperture radar (InSAR), yield phase images. These systems retrieve the phase up to a modulo-2π rad ambiguity, i.e., the phase is wrapped into the principal interval [-π π). Phase unwrapping (PU) is, then, a crucial inverse problem to obtain absolute phase, which is what embodies physical information. If the phase difference between neighboring pixels is less than π rad, then, phase unwrapping can be obtained unambiguously. This, however, is not always the case. For example, in InSAR, where absolute phase is proportional to the terrain elevation, we often face neighbor phase differences much larger than π rad. The PU problem is even more challenging for noisy images. This paper proposes a diversity approach, which consists of using two (or more) images of the same scene acquired with different frequencies. Diversity grants an enlargement of the ambiguity interval [-π π), thus, allowing to unwrap images with high phase rates. Furthermore, this paper presents a multi-resolution technique to make denoising. We formulate both tasks as integer optimization problems, which we tackle by using graph cuts techniques. We illustrate the effectiveness of our methodology by showing experimental results, which are, to our knowledge, state-of-the art competitive.