测试技术学报2024，Vol.38Issue(4)：401-406,6.DOI:10.3969/j.issn.1671-7449.2024051
基于梯度场和非局部均值的复杂工件图像增强算法
Image Enhancement of Complex Workpiece Based on Gradient Field and Non-Local Mean
摘要
Abstract
Due to the complexity of a highly dynamic X-ray imaging system and the complex structure of the workpiece itself,X-ray images often exhibit low contrast or unclear feature information.In this work,an image enhancement algorithm was proposed based on gradient field and non-local means to improve visual quality.A contrast adaptive enhancement model was constructed based on gradient field and local variance to improve the contrast of X-ray images;Then,the image was denoised using non-local means.Specifically,this paper constructed a non-local means algorithm based on Poisson distribution for image Poisson denoising,thereby obtaining an enhanced contrast field;Finally,an energy function was estab-lished and solved by using the gradient descent method to obtain higher quality images with small details.Experiments with two typical complex workpieces were performed,and the results verified the effective-ness of the proposed approach for image enhancement and defect detection.关键词
X射线成像/图像增强/梯度场/泊松分布/非局部均值Key words
X-ray imaging/image enhancement/gradient field/Poisson distribution/non-local means分类
信息技术与安全科学引用本文复制引用
韩美蓉,陈平,潘晋孝,李坤,陈洪..基于梯度场和非局部均值的复杂工件图像增强算法[J].测试技术学报,2024,38(4):401-406,6.基金项目
国家自然科学基金资助项目(62122070),信息探测与处理山西省重点实验室开放基金资助项目(2023-006) （62122070）
