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对原始数据进行粗量化的动态散斑分析。

Dynamic speckle analysis with coarse quantization of the raw data.

作者信息

Stoykova Elena, Nazarova Dimana, Nedelchev Lian, Ivanov Branimir, Blagoeva Blaga, Oh Kwan-Jung, Park Joongki

出版信息

Appl Opt. 2020 Mar 20;59(9):2810-2819. doi: 10.1364/AO.384204.

Abstract

Analysis of dynamic speckle formed on the surface of diffusely reflecting objects under laser illumination is a non-contact method for inspection of speed of processes. The paper deals with intensity-based implementation of the method that relies on statistical processing of correlated in time sequences of speckle images. A two-dimensional activity map is built for each sequence to visualize regions of different speed on the object surface at a given instant. A great number of images is required to track a process in time. We propose data compression by coarse quantization of the raw speckle data. Efficacy of quantization is analyzed by simulation and experiment for low- and high-contrast speckle patterns with bell-shaped and long-tailed distributions of intensity, respectively. Non-uniform quantization is proposed for long-tailed speckle intensity distributions. Decreasing the bit depth from 8 to 4 causes no change in the probability density function of the activity estimate.

摘要

分析激光照射下漫反射物体表面形成的动态散斑是一种用于检测过程速度的非接触式方法。本文讨论了该方法基于强度的实现方式,它依赖于对散斑图像的时间相关序列进行统计处理。为每个序列构建一个二维活动图,以可视化给定时刻物体表面不同速度的区域。为了及时跟踪一个过程,需要大量的图像。我们提出通过对原始散斑数据进行粗量化来进行数据压缩。分别针对具有钟形和长尾强度分布的低对比度和高对比度散斑图案,通过模拟和实验分析了量化的效果。对于长尾散斑强度分布,提出了非均匀量化。将比特深度从8位降低到4位不会导致活动估计的概率密度函数发生变化。

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