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CCD比色测温中辐射图像滤波与分割

孙元,彭小奇,宋彦坡(湖南第一师范学院信息科学与工程学院, 长沙 410205;湖南第一师范学院信息科学与工程学院, 长沙 410205;中南大学能源科学与工程学院, 长沙 410083)

摘 要
目的 高温热辐射图像存在较为严重的环境光、烟雾和粉尘干扰,因此图像滤波和分割是CCD比色测温法中实现准确测温的关键步骤。但传统的彩色图像处理方法不适合直接应用于辐射图像处理。方法 热辐射图像相邻像素间具有较强的相关性,为了量化表征不同空间距离像素颜色值之间的相互关联程度,设计了一种归一化空间距离加权函数,并与能同时滤除色调和亮度噪声的距离方向滤波器相结合,构建一种归一化空间距离加权距离方向滤波器。热辐射图像B基色接近于零,R、G基色分布在特定的直线方向上,且在该直线方向上呈现易于分割的双峰特性。为此提出利用Fisher准则构建R-G基色2维向量最佳1维投影,在1维空间利用最大类间方差法进行图像分割。结果 将本文方法与传统图像处理方法(采用距离方向滤波器滤波,彩色空间聚类法进行图像分割)进行比较,在高温工业炉上,经传统方法处理后的测量最大相对误差为1.99%,本文方法处理后为1.10%;在铜锍熔炼闪速炉上,传统方法最大相对误差为3.67%,本文方法为1.31%。经河南省计量院校验,基于本文方法构建的高温场测量仪在880℃~1 520℃的温度范围内测温最大绝对误差为4.2℃,最大相对误差为0.43%。结论 归一化空间距离加权使得滤波器在抑制冲击噪声的同时具有更好的保留细节的能力,图像分割算法能够克服与目标亮度相近的干扰,准确分割出待测目标。因此本文提出的图像处理方法能够有效克服高温辐射图像中的各种干扰,提高辐射测温的精确度和可靠性。
关键词
Radiation image filtering and segmentation in CCD-based colorimetric thermometry

Sun Yuan,Peng Xiaoqi,Song Yanpo(School of Information Science and Technology, Hunan First Normal University, Changsha 410205, China;School of Information Science and Technology, Hunan First Normal University, Changsha 410205, China;School of Energy Science and Engineering, Central South University, Changsha 410083, China)

Abstract
Objective The use of noncontact temperature measurements based on colored charge-coupled device (CCD) has significantly accelerated in recent years. However, the quality of radiation images is degraded by ambient light, smog, and dust interferences, and their suppression is indispensable to facilitate accurate measurements. Noise reduction and image target segmentation are regarded as key steps in colored CCD-based colorimetric thermometry. Nevertheless, traditional color image-processing methods are unsuitable for radiation images. Method In this work, an approach to the problem of impulsive noise removal and target segmentation in radiation images is presented. Given the strong spatial correlation among adjacent pixels in radiation images, a normalized spatial distance weighted function is designed to quantify the correlation degree among pixels in various distances. A normalized spatial distance weighted directional-distance filter is built based on the spatial distance weighted function and the directional-distance filter for the removal of color and light noises. In traditional filters, such as vector median, basic vector directional, and directional-distance filters, only the angle or distance among vectors is utilized. By contrast, the spatial distance of the vectors in a filtering window is considered in the normalized spatial distance weighted filter to alleviate the problems caused by the blurring properties of traditional filters. In radiation images, the blue color is nearly zero, whereas the red and green colors are distributed along a certain line with the double peak phenomenon. Traditional image segmentation algorithms fail because of the missing blue color information. In the proposed segmentation algorithm, the red and green two-dimensional color vectors are reduced to one dimension based on the optimal one-dimensional projection using the Fisher criterion. The measured target is segmented in the one-dimensional projection using Otsu’s method. The segmentation approach utilizes the red and green color information to conquer the interference with light that is similar to the target. Result The proposed method is compared with the traditional method of directional-distance filter and the clustering algorithm in color space. In a high-temperature heating furnace, the maximum absolute error is 1.99% using the traditional method, whereas the maximum absolute error decreases to 1.10% using the proposed method. In a copper-matte converting flash furnace, the maximum absolute errors are 3.67% and 1.31% using the traditional method and proposed method, respectively. A set of colored CCD-based colorimetric thermometry is designed by the proposed image-preprocessing method. The thermometry performance is examined with the blackbody furnace at the Henan Institute of Metrology. Experimental results show that the maximum absolute error is 4.2℃, and the maximum relative error is 0.43% of the thermometry in the measured range of 800℃~1 520℃. Conclusion The main advantage of the proposed normalized spatial distance weighted filter is its ability to suppress the noise component, while preserving image details. The proposed image segmentation approach overcomes the interferences whose brightness is close to the target image and segments the target accurately. The proposed radiation image-preprocessing method is characterized by low computational complexity, which enables the adaption of the novel technique in real-time temperature measurement.
Keywords
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