自适应维纳滤波在钢水红外图像去噪中的应用

翟潘; 王平

自适应维纳滤波在钢水红外图像去噪中的应用

翟潘,
王平

山东华宇工学院，山东德州 253011

基金项目:

山东省高等学校科技计划研究项目 J18KA378

详细信息

作者简介:
翟潘（1985-），男，硕士，讲师，主要研究方向为钢铁冶金自动化。E-mail: 2681043194@qq.com

中图分类号: TH811
计量
- 文章访问数: 234
- HTML全文浏览量: 94
- PDF下载量: 37
- 被引次数: 0
出版历程
- 收稿日期: 2019-12-01
- 修回日期: 2021-02-07
- 刊出日期: 2021-07-01

Application of the Adaptive Wiener Filter in Infrared Image Denoising for Molten Steel

ZHAI Pan,
WANG Ping

Shandong Huayu University of Technology, Dezhou 254011, China

摘要

摘要: 红外测温系统的应用减少了人工测温的安全事故，但其温度的准确性取决于由红外热像仪获得的图像的质量。为了对钢水红外图像质量的影响，提出了基于自适应维纳滤波的去噪方法。通过自相关的参数指数衰减模型来控制算法的计算复杂性和敏感性，进而有效提高维纳滤波器的去降噪性能。基于对不同温度下钢水红外图像的去噪处理，验证了所提去噪方法比维纳滤波和稀疏分解方法的图像去噪具有更好的去噪性能。
- 红外测温 /
- 图像去噪 /
- 自适应维纳滤波 /
- 红外辐射
Abstract: The application of an infrared temperature measurement system reduces the occurrence of safety accidents during manual temperature measurement. However, the accuracy of the measurement depends on the quality of the image obtained using the infrared thermal imaging camera. To reduce the influence of noise on the quality of molten steel infrared images, this paper proposes a denoising method based on adaptive Wiener filtering. The autocorrelation parameter exponential decay model is used to control the computational complexity and sensitivity of the algorithm, thereby effectively improving the denoising performance of the Wiener filter. Based on the denoising processing of molten steel infrared images at different temperatures, it is verified that the proposed denoising method has better denoising performance than Wiener filtering and sparse decomposition methods.
- infrared temperature /
- image denoising /
- adaptive wiener filtering /
- infrared radiation

HTML全文

图 1 钢水红外温度检测系统结构图

Figure 1. Structural diagram of molten steel temperature detection system

下载: 全尺寸图片幻灯片

图 2 1600℃的钢水红外图像去噪对比

Figure 2. Denoising comparison of molten steel infrared image at 1600℃

下载: 全尺寸图片幻灯片

图 3 1696℃的钢水红外图像去噪对比

Figure 3. Denoising comparison of molten steel infrared image at 1696℃

下载: 全尺寸图片幻灯片

表 1 用于温度修正的现场参数信息

Table 1. Information for temperature correction

Temperature/℃	25.0
Target distance/m	2.2
Atmospheric transmittance/%	100
Window transmittance/%	100
Global emissivity/%	62

下载: 导出CSV

表 2 不同温度下钢水红外图像去噪效果对比

Table 2. Comparison of denoising effect of molten steel infrared image under different temperatures

Noise processing method	MSE		PSNR/dB
Noise processing method	1600℃	1696℃	1600℃	1696℃
Wiener filter Sparse decomposition FIR wiener filter	0.1130 0.0906 0.0798	0.1261 0.1001 0.0805	10.235 18.539 25.683	10.095 19.168 26.956

下载: 导出CSV

表 3 钢水温度数据对比

Table 3. Comparison of the steel temperature data

Original image Fig.2(a)	1525
Denoised image using wiener filter Fig.2(b)	1556
Denoising image using sparse decomposition Fig.2(c)	1576
Denoising image using adaptive wiener filter Fig.2(d)	1591

下载: 导出CSV

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