摘要
射线数字成像是当前射线检测、诊断技术发展的重要方向,图像降噪增强是提高无损检测图像质量的关键。将基于小波变换的图像增强技术引入到射线无损检测(NDT)图像处理中,介绍了基于小波变换的反锐化掩模法、子带增强法和自适应增强法3种增强算法,并分别用这3种算法对射线NDT图像进行增强处理。通过对实验结果数据进行对比分析得出,相比另外两种小波增强算法,自适应小波增强算法处理后的图像更贴近实际,能够更好地在抑制图像噪声的同时增强图像细节。
Digital radiography is an important developmental tendency for radiographic inspection and diagnosis technique, and enhancement of image is the key to improve the quality of NDT images. Three image enhancement algorithms based on wavelet analysis to the NDT image enhancement were introduced. The unsharp masking algorithm, image sub-band enhancement algorithm and self-adapting enhancement algorithm based on wavelet analysis were discussed. Three algorithms were used to process a radiographic NDT order to enhance the NDT image. By comparing the results, self-adapting enhancement algorithm than the other two algorithms. Self-adapting enhancement algorithm can achieve an excellent balance the enhancement of subtle image detail and the avoidance of noise amplification .
出处
《半导体技术》
CAS
CSCD
北大核心
2007年第8期710-713,共4页
Semiconductor Technology
基金
中国博士后科学基金资助项目(2005038095)
山西省自然科学基金资助项目(20051043)
中北大学科学基金资助项目(2005)
关键词
NDT图像
小波变换
图像增强
自适应增强
NDT image
wavelet transform
image enhancement
self-adapting enhancement lnlage in is better between
