基于梯度场的工业X射线图像增强算法

在X射线成像检测厚薄不均构件时,经常会出现对比度低或对比度不均以及照度低的问题,这会导致图像显示时构件的一些细节难以被观察与分析。针对这一问题,提出一种基于梯度场的X射线图像增强算法。该算法以梯度场增强为核心,分为两步:首先,提出一种基于对数变换的算法,压缩图像的灰度范围、去除图像冗余灰度信息、提升图像对比度;然后,提出一种基于梯度场的算法,增强图像细节、提升图像局部对比度、提高图像质量,使构件细节清晰显示在检测屏上。选择一组厚薄不均构件的X射线图像进行了实验,并与对比度受限自适应直方图均衡化(CLAHE)、同态滤波等算法进行了比较。实验结果表明所提算法具有更明显的增强效果,能更好地显示构件的细节信息,并且通过计算平均梯度和无参考结构清晰度(NRSS)纹理分析的定量评价标准进一步表明了该算法的有效性。

Industrial X-ray image enhancement algorithm based on gradient field

In the detection of components with uneven thickness by X-ray, the problems of low contrast or uneven contrast and low illumination often occur, which make it difficult to observe and analyze some details of components in the images obtained. To solve this problem, an X-ray image enhancement algorithm based on gradient field was proposed. The algorithm takes gradient field enhancement as the core and is divided into two steps. Firstly, an algorithm based on logarithmic transformation was proposed to compress the gray range of an image, remove redundant gray information of the image and improve image contrast. Then, an algorithm based on gradient field was proposed to enhance image details, improve local image contrast and image quality, so that the details of components were able to be clearly displayed on the detection screen. A group of X-ray images of components with uneven thickness were selected for experiments, and the comparisons with algorithms such as Contrast Limited Adaptive Histogram Equalization (CLAHE) and homomorphic filtering were carried out. Experimental results show that the proposed algorithm has more obvious enhancement effect and can better display the detailed information of the components. The quantitative evaluation criteria of calculating average gradient and No-Reference Structural Sharpness (NRSS) texture analysis further demonstrate the effectiveness of this algorithm.