论文标题
基于Laguerre-Gaussian模式的光学图像分解和噪声过滤
Optical image decomposition and noise filtering based on Laguerre-Gaussian modes
论文作者
论文摘要
我们提出并实验证明了Laguerre-Gaussian（LG）域中有效的图像分解。通过开发高级计算方法，采样点要比现有方法中的采样点少得多，这可以显着提高计算效率。 LG模式的梁腰，方位角和径向截断顺序根据要恢复的图像信息进行了优化。在实验中，我们通过使用约30000 LG模式分解图像，并实现高保真重建。此外，我们通过LG域滤波显示了图像降噪。我们的结果为基于LG模式的图像处理打开了门。
We propose and experimentally demonstrate an efficient image decomposition in the Laguerre-Gaussian (LG) domain. By developing an advanced computing method, the sampling points are much fewer than those in the existing methods, which can significantly improve the calculation efficiency. The beam waist, azimuthal and radial truncation orders of the LG modes are optimized depending on the image information to be restored. In the experiment, we decompose an image by using about 30000 LG modes and realize a high-fidelity reconstruction. Furthermore, we show image noise reduction through LG domain filtering. Our results open a door for LG-mode based image processing.
