基于BEMDV方法的数字全息的重建图像中的噪声抑制,使用改进的粒子群集优化
Applied optics
|September 14, 2023
概括
本研究引入了一种用于数字全息的新降噪技术,它结合了二维实证模式分解 (BEMD) 和变化方法. BEMDV方法通过减少斑点噪声和保存细节,显著提高了重建的图像质量.
科学领域:
- 光学和光子学 在光学和光子学.
- 图像处理 图像处理
背景情况:
- 数字全息画中的斑点噪声降低了重建的图像质量.
- 一致的光源和光散射导致全息系统中的噪声.
研究的目的:
- 为数字全息画提出一种新的降噪方法.
- 为了提高重建的全息图像的质量.
主要方法:
- 提出了一种新的方法,BEMDV,它结合了二维实证模式分解 (BEMD) 和变化方法.
- 使用BEMD将图像分解为内在模式函数 (IMF),并通过变化方法处理所选的IMF.
- 改进的粒子群优化算法优化了降噪的关键参数.
主要成果:
- 与一般方法相比,BEMDV方法证明了优越的降噪.
- 拟议的方法在降噪期间有效保存图像细节.
- 硬币和光学分辨率板全息图的实验结果验证了该方法的性能.
结论:
- 在BEMDV方法显著提高全息图像重建质量.
- 这种技术提供了一个强大的解决方案,用于减少数字全息画中的斑点噪声.
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