Information Entropy Analysis of a PIV Image Based on Wavelet Decomposition and Reconstruction

IF 2.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Entropy Pub Date : 2024-06-30 DOI:10.3390/e26070573

Zhiwu Ke, Wei Zheng, Xiaoyu Wang, Mei Lin

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引用次数: 0

Abstract

In particle image velocimetry (PIV) experiments, background noise inevitably exists in the particle images when a particle image is being captured or transmitted, which blurs the particle image, reduces the information entropy of the image, and finally makes the obtained flow field inaccurate. Taking a low-quality original particle image as the research object in this research, a frequency domain processing method based on wavelet decomposition and reconstruction was applied to perform particle image pre-processing. Information entropy analysis was used to evaluate the effect of image processing. The results showed that useful high-frequency particle information representing particle image details in the original particle image was effectively extracted and enhanced, and the image background noise was significantly weakened. Then, information entropy analysis of the image revealed that compared with the unprocessed original particle image, the reconstructed particle image contained more effective details of the particles with higher information entropy. Based on reconstructed particle images, a more accurate flow field can be obtained within a lower error range.

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基于小波分解和重建的 PIV 图像信息熵分析

在粒子图像测速（PIV）实验中，采集或传输粒子图像时不可避免地会存在背景噪声，这会模糊粒子图像，降低图像的信息熵，最终使获得的流场不准确。本研究以低质量的原始粒子图像为研究对象，采用基于小波分解和重构的频域处理方法对粒子图像进行预处理。采用信息熵分析评估图像处理效果。结果表明，原始粒子图像中代表粒子图像细节的有用高频粒子信息得到了有效提取和增强，图像背景噪声明显减弱。然后，对图像进行信息熵分析发现，与未经处理的原始粒子图像相比，重建后的粒子图像包含了更多有效的粒子细节，信息熵更高。基于重建后的粒子图像，可以在较小的误差范围内获得更精确的流场。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Entropy PHYSICS, MULTIDISCIPLINARY-

CiteScore

4.90

自引率

11.10%

发文量

1580

审稿时长

21.05 days

期刊介绍： Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.