Ultrasonic Imaging for Boundary Shape Generation by Phase Unwrapping with Singular-Point Elimination Based on Complex-Valued Markov Random Field Model
Ultrasonic imaging is useful in seabed or lakebed observations. We can roughly estimate the sea depth by hearing the echo generated by the boundary of water and rocks or sand. However, the estimation quality is usually not sufficient to draw seabed landscape since the echo signal includes serious distortion caused by autointerference. This paper proposes a novel method to visualize the shape of distant boundaries, such as the seawater-rock/sand boundary, based on the complex-valued Markov random field (CMRF) model. Our method realizes adaptive compensation of distortion without changing the global features in the measurement data, and obtains higher-quality landscape with less computational cost than conventional methods.
acoustics adaptive signal processing markov process phase measurement seabed observation