基于像素值分布统计的数字全息再现像优化

Optimization of digital holographic reconstruction image based on pixel value distribution statistics

拉普拉斯算子经傅里叶变换,可得到一个带通滤波窗口,将其运用于无透镜傅里叶变换数字全息再现可以有效去除零级像,但在中心区域,仍存在部分零级像残余。提出一种新的方法,该方法结合再现像的像素值分布统计,通过合理设定阈值,能有效地去除零级像残余,同时抑制散斑噪声。理论和实验分析表明,该方法可行有效。

The Laplace operator after Fourier transform, can be used as a band-pass filter window. In the reconstruction of lensless Fourier transform digital holographic, the zero-order image can be removed based on the filtering window. However, the reconstruction still exist lots of zero-order image residuals in the central area. In this paper, an improved method is proposed. Combining with the pixel value distribution statistics of the reproduced image, this method can effectively remove the zero-order image residuals and suppress the speckle noise by setting the thresholds reasonably. Theoretical and experimental analysis shows that this method is feasible and effective.