Improving phase-unwrapping result of InSAR images by incorporating the fractal model

This paper presents a novel method to reduce the phase-unwrapping (PU) distortion by being based on two-dimensional fractional Brownian motion (fBm) theory. The method incorporates fractal geometry estimation to the result of conventional global-transform PU (GTPU). For the spatial-frequency spectrum of an observed phase image, we estimate the fractal dimension, by assuming an almost constant dimension over the image, and compensate the distorted spectrum of a GTPU result. It is demonstrated that the proposed method increases the signal-to-noise ratio of PU results for simulated data with various noise levels. Evaluations on an actual InSAR phase image also show that the method significantly improves the quality of the conventional GTPU result in its fine structure in particular.