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    Area of Science:

    • Spatial algorithms
    • Computational imaging
    • Data processing

    Background:

    • Quality-guided phase unwrapping is widely used for its efficiency and robustness.
    • Existing methods often depend on quality map data distribution, limiting their application in time-sensitive scenarios.
    • Improvements are needed for real-time processing in demanding applications.

    Purpose of the Study:

    • To propose a novel pruning strategy for quality-guided phase unwrapping.
    • To develop an algorithm with computational time independent of quality map distribution.
    • To enable real-time phase unwrapping for time-varying phase distribution experiments.

    Main Methods:

    • Implementation of a novel pruning strategy using a red-black tree data structure.
    • Leveraging the partial ordering of red-black tree branches for accelerated unwrapping.
    • Testing the algorithm with real and simulated interferometric data.

    Main Results:

    • The proposed red-black tree-based pruning strategy demonstrates improved computational time complexity.
    • Performance is independent of the quality map's value distribution.
    • Successful processing of time-varying phase distribution experiments for real-time applications.

    Conclusions:

    • The novel red-black tree pruning strategy significantly enhances quality-guided phase unwrapping efficiency.
    • The algorithm's independence from quality map distribution makes it robust and versatile.
    • The method is suitable for real-time applications, with publicly available source code.