数字射线图像降噪中的非线性滤波方法

阐述了几种常用于数字射线成像信息处理的非线性滤波降噪法,包括中值滤波、同态滤波、小波降噪和形态滤波法。并通过试验进行了分析比较,得出各种方法的优缺点及适用场合。介绍了一些较新颖的降噪方法,为处理射线检测图像提供一个参考依据。     

X射线平板探测器的成像噪声消除方法

针对X射线平板探测器的实时成像检测系统,分析噪声来源,研究消除随机噪声的方法,利用了多帧叠加,平滑滤波的线性、非线性滤波等方法,对实验测试得到的图像进行降噪处理,结果表明:该方法的降噪效果较好,为解决射线实时检测过程的图像降噪问题奠定了基础.     

数字射线图像降噪中的线性滤波方法

数字射线成像(DR)系统中,图像中的噪声是影响图像质量的重要因素之一,给图像分析和缺陷(尤其是微细瑕疵)识别带来了困难。为了提高图像的信噪比,对图像降噪方法的研究是十分必要的。对DR系统中噪声的来源及其产生的影响进行分析后,比较了几种常用的线性滤波方法对射线图像的降噪效果,介绍了近年来提出的一些较新颖的降噪方法。     

采用数字射线DR成像的焊接质量检测

提出了一种基于数字射线成像的焊缝质量检测方法。采用先进的非晶硅数字检测系统获取信息丰富的原始图像,叠加曝光降低图像噪声;依据射线衰减的指数规律对图像进行对数解调,凸现缺陷特征;运用非锐化掩模滤波对特征进行增强。使焊缝缺陷特征清晰,检测质量达到胶片最高级B级水平。     

工业射线视频成像的噪声抑制方法

介绍了X射线图像增强器视频成像系统的结构和性能,分析了影响成像质量的因素.转换屏和CCD成像系统响应的不一致性是影响检测灵敏度的主要因素;而由于量子起伏、散射等造成的随机噪声也严重影响了成像质量.文中先对系统的不一致性进行模型校正,再针对随机噪声进行递归滤波降噪,与单一方法的噪声抑制相比,有效地提高了系统的成像质量.     

射线检测底片缺陷图像的预处理技术

图像识别技术是人工智能在焊缝射线检测技术领域的典型应用场景之一,开展图像识别技术在工业焊缝检测和智能监测中的研究和应用,对推动无损检测智能化发展具有重要意义。射线检测底片缺陷图像预处理能够在短时间内将复杂图片简单化,为后续的缺陷识别打好基础。X射线检测原始图像灰度区间窄,对比度低,噪声大,为解决这一问题,采用不同的降噪处理与对比度增强图片预处理方法,开展了射线检测底片预处理试验,并根据实际检测效果优化了参数,改进了算法。试验结果表明,降噪方面,中值高斯组合滤波的降噪效果较好;对比度增强方面,线性变换的对比度增强效果较好。     

一种新型焊接质量数字射线检测技术

研究了基于非晶硅面阵探测器的对焊缝数字射线检测技术。分析了探测器性能,提出了选择探测器参数的原则,并建立探测器校正模型;使其由响应不一致性导致的图像的降质减少,针对数字成像噪声大的特点,采取了叠加平均时间城上的序列帧图像,既降低了噪声,又避免了降噪的同时会模糊焊缝缺陷特征的矛盾;对焊缝中的微细缺陷,运用非锐化掩模滤波算法加强其微细缺陷特征,提高了微细缺陷的可分辨性。     

X射线线阵实时成像焊缝缺陷检测方法

针对X射线线阵探测器实时成像的焊缝图像,提出了降噪处理、焊缝图像分割及缺陷检测的方法.通过自适应中值滤波方法对焊缝图像进行滤波降噪,利用类间、类内方差比分割法和数学形态学方法进行焊缝图像分割,对焊缝部分应用高频加强变换提取焊接缺陷.结果表明,采用自适应中值滤波能够有效去除噪声的同时保留焊缝和缺陷的边缘细节;类间、类内方差比分割方法与数学形态学方法并用能准确地将图像分割为焊缝与母材区域;高频加强变换能使焊缝中心部位灰度变化突显进而实现缺陷检测.     

卷绕锂电芯的X射线成像特点及图像处理技巧

介绍了卷绕型锂电芯的X射线检测方案及其成像特点,结合工业自动检测快速准确的需要,提供了包括图像滤波、极线追踪、模糊图像处理等过程的快速算法,并在卷绕电芯的实际X射线检测图像中验证。     

一种X射线图像增强方案

X射线图像信息量大,通常不止一个灰度层次,运用图像增强方法可以提高图像对比度和像质,达到细节区域的最佳视觉效果。笔者首先分析了图像直方图层次;然后针对不同层次的图像内容,采用模糊松弛迭代算法建立了模糊集映射函数,对射线图像进行迭代运算;最后,使用迭代处理结果进一步做Sobel边缘检测算子处理和均值滤波处理。试验表明,该算法增强了图像视觉效果,且增强了图像中不同灰度层次的边缘细节信息,使得图像层次感更加明显。     

Computerized laminagraphy

Laminagraphy is a radiographic technique used to image cross-sectional views through solid objects. Coplanar rotational laminagraphy (CRL) is a special case where the film and object rotate synchronously while the radiation source remains stationary. The orientation of the radiographic film corresponds to the cross-sectional slice through the object being imaged. The image formed on the exposed film is highly blurred owing to the continuous summation of radiographic projections taken at different angles through the object. Theoretical analysis of the image formation process shows that the resultant image is simply a convolution of the ideal cross-sectional image with a radially symmetric point spread function having the form r⁻¹. Direct deconvolution does not give good results since image noise becomes a significant factor owing to the high-frequency amplification of the deconvolution operator. A parametric filter based on the optimized Wiener restoration filter is shown to provide good results for a few selected specimens.     

Optimal signal-adaptive maximum likelihood filter for enhancement of defects in eddy current C-scan images

True estimation of the boundary and size of defects are major problems in eddy current (EC) non-destructive evaluation of conductive materials. EC image processing techniques can be used for better estimation of defect details. Because of non-stationary nature of EC C-scan images and same intensities of noise and defect histograms, the linear techniques do not produce good results. In this paper a non-linear signal-adaptive filter based on maximum likelihood (SAML) criterion is designed and successfully used for defect detection. The model of EC noise in this filter is assumed to be non-zero mean complex Gaussian process. The desired model of SAML (MSAML) filter is also modified to further reduce the probability of error and enhance defect details and boundary realization. Simulated and experimental results demonstrate the successful performance of the SAML and MASML filters in estimation of defect details and noise removal.     

基于整形多卡尔曼滤波模型的GPS实时变形分析(英文)

提出的整形多卡尔曼滤波模型可进行形变的实时检测并提高其可靠性。多卡尔曼滤波模型的扩展主要针对GNSS时间形变序列含有有色噪声的情况,而多卡尔曼滤波模型只能应用于白噪声的情况下,故采用整形滤波扩展多卡尔曼滤波模型去除有色噪声的影响。提出的模型可以提高结果的精度且实时进行变形监测,可用于灾害预警系统。通过对比该模型与其他模型(卡尔曼滤波模型,整形卡尔曼滤波模型,多卡尔曼滤波模型)发现,所改进的模型在检测形变的实时性和可靠性方面优于其他模型。     

Image processing of ESPI based on measurement the welding dynamic displacement fields

A dual-beam electronic speckle pattern inteorerometry (ESPI) system was adopted to get speckle patterns for the measurement of welding dynamic displacement fields. The mathematical model of this system was described, based on which methods of the ESPI pattern image processing were discussed. Gray transformation and histogram equalization were used to enhance the contrast of speckle patterns. A discrete cosine image processing method was carried out and an exponent low-pass filter was chosen to reduce multiplicative noise in speckle patterns. Speckle grain noise can be eliminated effectively after these processes.     

射线实时成象中图象拼接技术的研究

指出了射线实时成象中国象拼接的重要性,分析了对图象匹配的算法和减小计算量的措施,对图象拼接的方法进行了研究,提出了在被测对象发生了旋转的情况下进行拼接的“特征线”法,为大型被测对象的整体检测创造了条件。     

复合材料剪切散斑检测图像的小波降噪技术研究

电子剪切散斑检测技术非常适宜复合材料的无损检测。散斑图像往往含有较大的噪声,如何对散斑图像进行降噪处理是一个非常重要的问题。小波变换是变分辨率的分析方法,用小波降噪技术处理散斑图像可以有效地降低噪声,同时能较好地保存图像细节。     

微间隙焊缝磁光成像NN-KF跟踪算法分析

针对紧密对接微间隙焊缝,分析基于磁光成像的神经网络补偿卡尔曼滤波（kalman filtering compensated by neural network,NN-KF）跟踪算法,建立焊缝位置测量模型并运用卡尔曼滤波对焊缝位置偏差进行最优预测.卡尔曼滤波进行最优估计需建立准确的系统模型和观测模型,而在焊缝跟踪过程中,系统噪声具有非先验性.对于针对测量模型误差、过程噪声和测量噪声对卡尔曼滤波结果的影响,运用反向传播（back propagation,BP）神经网络对卡尔曼滤波结果进行修正,补偿模型误差及噪声统计不确定性造成的滤波误差.结果表明,BP神经网络补偿卡尔曼滤波算法能有效抑制滤波发散,减小噪声干扰影响,提高焊缝跟踪精度.     

Circular discontinuities detection in welded joints using Circular Hough Transform

Conventional radiography is one of the common non-destructive testing which employs manual image interpretation. The interpretation is very subjective and depends much on the inspector experience and working conditions. It is therefore useful to have pattern recognition system in order to assist human interpreter in evaluating the quality of the radiographed sample, especially radiographic image of welded joint. This paper describes a system to detect circular discontinuities that are present in the joints. The system utilizes together two different algorithms, which are separability filter to identify the best object candidate and Circular Hough Transform to detect the presence of circular shape. The result of the experiment shows a promising output in recognition of circular discontinuities in a radiographic image. This is based on 81.82–100% of radiography film with successful circular detection by using template movement of 10 pixels.