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基于三元光学计算机的并行OTSU算法的设计和实现.

Kai Song, Yongjun Sun, Huaqiong Ma

    Applied optics
    |December 18, 2023
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    概括
    此摘要是机器生成的。

    本研究介绍了一种平行OTSU算法,用于在三元光学计算机 (TOC) 上进行图像细分. 在图像处理任务中,TOC实现将计算速度提高约12%.

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    科学领域:

    • 计算机科学 计算机科学
    • 图像处理 图像处理
    • 光学计算是指光学计算的应用.

    背景情况:

    • OTSU方法是用于图像分割值选择的标准.
    • 传统计算机在OTSU算法下面面临速度和存储限制.
    • 三级光学计算机 (TOC) 在数据处理和处理方面提供了潜在的优势.

    研究的目的:

    • 开发一个平行OTSU算法,优化TOC.
    • 为了利用TOC的并行处理能力来实现更快的图像分割.
    • 在TOC上评估并行OTSU算法的性能改进.

    主要方法:

    • 分析OTSU算法以识别可并行的组件.
    • 在TOC架构上实现并行OTSU算法.
    • 修改后的符号数字 (MSD) 加数和乘数的重建,用于并行计算.
    • 像素分类和并行计算类间差异.

    主要成果:

    • 开发了一个适合TOC的并行OTSU算法.
    • 平行算法实现了大约12%的计算速度增加.
    • TOC的实施证明了图像数据的有效并行处理.

    结论:

    • 在TOC上的并行OTSU算法显著提高了图像分割的处理速度.
    • TOCs是加速像OTSU这样的计算密集型图像处理算法的可行平台.
    • 这项研究突出了光学计算在数字图像处理应用中的潜力.