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A Shared-Memory Parallel Alpha-Tree Algorithm for Extreme Dynamic Ranges.

Jiwoo Ryu, Scott C Trager, Michael H F Wilkinson

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
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    Summary
    This summary is machine-generated.

    This study introduces a faster parallel algorithm for the alpha-tree ($\alpha $-tree), a hierarchical image representation crucial for remote sensing image analysis. The novel hybrid approach significantly speeds up processing, especially for complex, high dynamic range images.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Remote Sensing

    Background:

    • The alpha-tree ($\alpha $-tree) is an effective hierarchical image representation for connected filtering and segmentation.
    • It offers superior image granularity representation and easier multichannel application compared to methods like the component tree.
    • A key limitation of the $\alpha $-tree is its slow processing speed, particularly for multichannel and high dynamic range images.

    Purpose of the Study:

    • To develop a novel, fast, and parallel algorithm for constructing the alpha-tree ($\alpha $-tree).
    • To adapt the hybrid component tree algorithm for efficient $\alpha $-tree construction across all dynamic ranges of pixel dissimilarity.
    • To address the processing speed limitations of the traditional $\alpha $-tree algorithm.

    Main Methods:

    • A novel adaptation of the hybrid component tree algorithm was applied to the $\alpha $-tree construction.
    • The hybrid $\alpha $-tree algorithm was implemented and tested on a high-performance computing cluster (Hábrók).
    • Experiments utilized Sentinel-2 remote sensing images and randomly generated images to evaluate performance.

    Main Results:

    • The hybrid $\alpha $-tree algorithm achieved processing speeds of 10-30 Megapixels/second.
    • A significant speedup of 10-30 times was observed on a 128-core computer.
    • This represents the first known parallel $\alpha $-tree algorithm capable of handling high dynamic range images efficiently.

    Conclusions:

    • The developed hybrid $\alpha $-tree algorithm offers a substantial improvement in processing speed.
    • The algorithm is efficient for parallel processing of high dynamic range images in remote sensing applications.
    • This work overcomes previous limitations and enables faster, more scalable image analysis using the $\alpha $-tree representation.