基于梯度场的工业X射线图像增强算法

doi:10.11772/j.issn.1001-9081.2019040694

计算机应用 ›› 2019, Vol. 39 ›› Issue (10): 3088-3092.DOI: 10.11772/j.issn.1001-9081.2019040694

• 应用前沿、交叉与综合 • 上一篇下一篇

基于梯度场的工业X射线图像增强算法

周冲, 刘欢, 赵爱玲, 张鹏程, 刘祎, 桂志国

生物医学成像与影像大数据山西省重点实验室(中北大学), 太原 030051

收稿日期:2019-04-23 修回日期:2019-07-02 发布日期:2019-08-21 出版日期:2019-10-10
通讯作者: 桂志国
作者简介:周冲(1994-),男,湖北洪湖人,硕士研究生,主要研究方向:X射线图像处理、神经网络;刘欢(1994-),男,四川南充人,硕士研究生,主要研究方向:CT重建、图像处理;赵爱玲(1995-),女,山西大同人,硕士研究生,主要研究方向:X射线图像处理、神经网络;张鹏程(1984-),男,内蒙古巴彦淖尔人,讲师,博士,主要研究方向:精准放射治疗剂量计算及方案优化;刘祎(1987-),女,河南睢县人,讲师,博士,主要研究方向:图像处理、图像重建;桂志国(1972-),男,天津人,教授,博士,主要研究方向:三维CT理论与工程应用、医学图像处理与重建、模式识别。
基金资助:
国家自然科学基金资助项目（61671413，61801438）；国家重大科学仪器设备开发专项（2014YQ24044508）；山西省应用基础研究项目（201801D221196）；中北大学青年学术带头人项目（QX201801）。

Industrial X-ray image enhancement algorithm based on gradient field

ZHOU Chong, LIU Huan, ZHAO Ailing, ZHANG Pengcheng, LIU Yi, GUI Zhiguo

Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data(North University of China), Taiyuan Shanxi 030051, China

Received:2019-04-23 Revised:2019-07-02 Online:2019-08-21 Published:2019-10-10
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61671413, 61801438), the National Key Scientific Instrument and Equipment Development Project of China under Grant (2014YQ24044508), the Shanxi Applied Basic Research Project (201801D221196), the Young Academic Leadership Program of North University of China (QX201801).

摘要/Abstract

摘要： 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。

关键词: 图像增强, X射线, 梯度场, 对数变换, 直方图

Abstract: 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.

Key words: image enhancement, X-ray, gradient field, logarithmic transformation, histogram

中图分类号:

TP391.41

周冲, 刘欢, 赵爱玲, 张鹏程, 刘祎, 桂志国. 基于梯度场的工业X射线图像增强算法[J]. 计算机应用, 2019, 39(10): 3088-3092.

ZHOU Chong, LIU Huan, ZHAO Ailing, ZHANG Pengcheng, LIU Yi, GUI Zhiguo. Industrial X-ray image enhancement algorithm based on gradient field[J]. Journal of Computer Applications, 2019, 39(10): 3088-3092.

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基于梯度场的工业X射线图像增强算法

Industrial X-ray image enhancement algorithm based on gradient field

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