一种混合过方法,用于对合成光圈声纳图像进行无参考质量评估
Zhiping Xu1,2, Deyin Xu1, Yisong He1
1School of Ocean Information Engineering, Jimei University, Xiamen, China.
PloS one
|November 18, 2025
概括
本研究引入了一种新的混合过方法,并对合成孔径声纳 (SAS) 图像进行无参考质量评估. 新方法改善了噪音抑制,并比现有的过技术更好地保存图像细节.
科学领域:
- 海洋技术 海洋技术
- 信号处理 信号处理
- 图像分析 图像分析
背景情况:
- 合成孔径声纳 (SAS) 成像对于水下应用至关重要.
- 现有的SAS图像的过方法在噪声抑制,细节退化和边缘模糊方面扎.
- 目前对SAS图像过的质量评估往往是主观的,阻碍了研究.
研究的目的:
- 为SAS图像提出一种新的混合过方法.
- 为评估SAS图像过技术开发一个无参考的质量评估.
- 克服现有的过方法和质量评估的局限性.
主要方法:
- 一种两阶段的混合过方法:局部统计干扰抑制,然后进行加权光滑以保护边缘.
- 开发SAS图像的无参考质量评估指标.
- 对拟议的混合过器与中值和平均值过器进行比较分析.
主要成果:
- 无参考质量评估有效地评估了不同的过方法.
- 拟议的混合过方法与传统方法相比,显示出更高的性能.
- 新方法实现了更好的噪音抑制,同时保留了关键的图像细节和边缘.
结论:
- 拟议的混合过方法为SAS图像处理提供了显著的改进.
- 无参考质量评估为过器评估提供了一个客观有效的工具.
- 这项工作推动了用于水下SAS成像的有效过技术的开发.
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