Translation-Invariant Tile-Based Phase Unwrapping with Residual-Weighted Multipath Averaging

2026-09-11

AI Summary

本文提出了一种基于平移不变的分块相位解缠方法，通过DCT和最小二乘法在频域内解缠，并结合残差加权多路径平均来解决噪声、不连续性等问题。

Abstract

Phase unwrapping is a key step in interferometric and coherent imaging, where the physical quantity of interest is carried by a phase that the instrument delivers only modulo 2*pi. The difficulty in two dimensions is to separate the jumps caused by wrapping from those produced by noise, by true discontinuities, by under-sampling or by decorrelation. Spatial-domain and frequency-domain methods have both been studied extensively, each with advantages the other lacks; hybrid schemes combining the two remain scarce. We propose a semi-global tile-based strategy in which every tile is unwrapped in the frequency domain, through the Discrete Cosine Transform (DCT) and the least squares (LS) formalism of Ghiglia et al., the tiles being merged spatially. Unwrapping and noise filtering are performed jointly, which regularizes an otherwise ill-posed inverse problem. An error stays confined to the tile in which it arose; the tiling artifacts are removed by averaging over every shift of the grid and over the symmetries of the square; and that average is weighted by the Poisson residual each pass leaves behind, so that a pass whose tile boundaries fell on a discontinuity does not impose its seam on the result. Experiments on synthetic and real data, against four reference algorithms from four distinct families and under six complementary metrics, show that the proposed method matches or improves on the state of the art. One of these metrics, a corrected cyclic re-wrap residual introduced here, needs no ground truth and therefore remains available on real acquisitions.

Problem

• Phase Unwrapping
• Interferometric Imaging
• Coherent Imaging
• Discontinuities
• Noise

Innovation

• Translation-Invariant
• Tile-Based Phase Unwrapping
• Residual-Weighted Multipath Averaging
• Discrete Cosine Transform (DCT)
• Least Squares (LS)