> ## Documentation Index
> Fetch the complete documentation index at: https://felimet-hub.jmcores.com/llms.txt
> Use this file to discover all available pages before exploring further.

# 溫度異質性對氣流對流影響的視覺化因果分析

> Automation 2024 研討會論文，結合彩色紋影與紅外線熱影像，運用暗通道先驗（DCP）與 NLIDA 除霧演算法強化氣流結構可視化，並透過因果分解分析溫度異質性對氣流對流模式的影響，榮獲學生論文獎第二名。

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<PubMeta type="conference" venue="The 21th International Conference on Automation Technology (Automation 2024)" date="2024-11-22" confType="Oral" />

# Visual Causal Analysis of the Impact of Temperature Heterogeneity on Airflow Convection

Jia-Ming Zhou, Wen-Lin Chu, and Jun-Ye Luo

\*Corresponding author: Bo-Lin Jian

## 摘要 Abstract

本研究提出一套新穎的彩色紋影系統，能夠透過影像色彩直接觀測溫度，並同步使用紅外手持式熱影像儀擷取溫度變化進行驗證。
本研究對紋影影像應用兩種除霧方法以強化氣流細節：暗通道先驗法（DCP）與非局部影像除霧演算法（NLIDA）。研究結果顯示，
NLIDA 在增強氣流的色彩與細節方面表現卓越，而 DCP 在分析氣流與溫度的相關性時則更為準確。
跨四種色彩空間（RGB、HSV、Lab\*、YUV）的分析顯示，經 DCP 處理的影像在多個通道中與溫度呈現高度相關性（相關係數絕對值 > 0.8）。
此外，本研究採用因果分解演算法探討氣流與溫度變化對紋影影像色彩的影響關係。
因果分析證實熱變化會影響紋影形成，確認溫度變化為紋影影像生成的關鍵因子。
最後，本研究開發一套互動式圖形化使用者介面（GUI）以視覺化呈現因果關係分析結果，促進直觀的資料詮釋。

This study introduces a new color schlieren system that can directly observe temperature through image
color and simultaneously capture temperature changes using an infrared handheld thermal imager for verification.
We applied two dehazing methods to the Schlieren images to enhance airflow
details: the Dark Channel Prior (DCP) and the Non-Local Image Dehazing Algorithm (NLIDA). Our results
demonstrate that NLIDA excels in enhancing the colors and details of the airflow, whereas DCP proves more accurate
in analyzing the correlation between airflow and temperature. Analysis across four color spaces (RGB, HSV, Lab\*,
YUV) reveals that DCP-processed images exhibit a high correlation with temperature in multiple channels (correlation
coefficient absolute value > 0.8). Furthermore, we employed a causal decomposition algorithm to investigate the
relationship between airflow and temperature changes on Schlieren image colors. The causal analysis confirms that
thermal variations influence schlieren formation, identifying temperature changes as a critical factor in schlieren image
production. Finally, we developed an interactive Graphical User Interface (GUI) to visualize the results of the causal
relationship analysis, facilitating intuitive data interpretation.

## 關鍵字 Keywords

* 彩色紋影技術 Color Schlieren Technique
* 暗通道先驗 Dark Channel Prior (DCP)
* 非局部影像除霧演算法 Non-Local Image Dehazing Algorithm (NLIDA)
* 聚類分析 Clustering Analysis
* 因果分析 Causal Analysis

## 研究結果示例

<img src="https://mintcdn.com/felimet/o4nUK2uwNPSF27VA/images/auto2024_demo.png?fit=max&auto=format&n=o4nUK2uwNPSF27VA&q=85&s=b8cb5b7b2182dd17cf7aa5500cfd775c" alt="Demo" width="3081" height="1302" data-path="images/auto2024_demo.png" />

## 引用格式 BibTeX

<CiteSwitch
  bibtex={`@inproceedings{zhou2024automation,
author    = {Jia-Ming Zhou and Wen-Lin Chu and Jun-ye Luo},
title     = {Visual Causal Analysis of the Impact of Temperature Heterogeneity on Airflow Convection},
booktitle = {The 21th International Conference on Automation Technology (Automation 2024)},
year      = {2024},
month     = {November},
address   = {Taipei, Taiwan}
}`}
/>