An Application of Continuous Weights to Phase Unwrapping

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  • Application of Continuous Weights to Phase Unwrapping

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Two-dimensional phase unwrapping is a key step in extraction of digital elevation models (DEMs) from interferometric synthetic aperture radar (IFSAR) data. Least-squares (LS) algorithm is one of major approaches to phase unwrapping, and weighted LS algorithm offers great potential if weights are appropriately obtained. However, the determination of weights is still a critical problem. As noise increases, binary weights becomes more difficult to be determined, because of high possibility of coexisting of noise pixels and non-noise pixels in same histogram bin. Hence instead of determining binary weights, this paper presents an effective approach to determining continuous weights by incorporating weighted LS algorithm into a minimization method. The continuous weights are estimated by minimizing a norm of the differences between real values and calculated ones. The proposed approach is illustrated through a simulative example in which the input data are corrupted by both uniformly distributed noise and scattered noise. By comparing errors of phase unwrapping by binary weights and those by continuous weights, the latter turns out to be superior to the former.

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