CHENG Yanmei,LIU Zhihong.X-ray Image Processing based on CLAHE FusionEdge Detail Enhancement Algorithm[J].Journal of Chengdu University of Information Technology,2020,35(06):621-624.[doi:10.16836/j.cnki.jcuit.2020.06.007]
CLAHE融合边缘细节增强算法的X光图像处理
- Title:
- X-ray Image Processing based on CLAHE Fusion Edge Detail Enhancement Algorithm
- Keywords:
- histogram equalization; image enhancement; X-ray chest radiograph; edge enhancement; evaluation index
- 分类号:
- TP751.1
- 文献标志码:
- A
- 摘要:
- 针对某些医疗器械设备在图像采集过程中,因人体结构和组织的复杂性以及噪声、X线散射等不可抗因素导致X光图像质量差、对比度低的问题,利用限制对比度直方图均衡算法结合边缘细节增强算法对胸部X光图像进行增强操作。首先,使用对比度直方图均衡算法对灰度图像进行图像增强,有效地增强了图像清晰度并抑制了噪声的放大,然后在图像灰度值跳变部分通过卷积的原理对图像进行细节增强,最后利用信息熵、平均梯度、标准差等指标对图像增强效果进行客观评价。实验表明,该方法在胸片图像增强上有显著效果,增强后的图像纹理特征和细节对比明显,图像质量得到很大提高。
- Abstract:
- In order to solve the problem of poor quality and low contrast of X-ray images due to the complexity of human body structure and tissue, as well as force majeure factors such as noise and X-ray scattering in the image acquisition process of some medical equipment. This paper uses the contrast histogram equalization algorithm combining the edge detail enhancement algorithm to enhance the chest X-ray image. First, the grayscale image is enhanced by the contrast histogram equalization algorithm, which effectively enhances the image clarity and suppresses the amplification of noise. Then, the details of the image are enhanced by the principle of convolution at the transition of the grayscale value. Finally, indicators such as information entropy, average gradient, and standard deviation are used to objectively evaluate the image enhancement effect. Experiments show that the method in this paper has a significant effect on the enhancement of chest radiograph images. The enhanced image texture features and details have higher contrast, and the image quality is greatly improved.
参考文献/References:
[1] 杨晖,翟丽荣.X线医学图像的对比度增强方法与实现[J].辽宁大学学报(自然科学版),2009,36(1):64-66.
[2] 吴君,阳建华,贺超,等.图像增强技术在数字X射线医学影像中的应用[J].中国医学装备,2012,9(5):60-62.
[3] 李小飞.基于直方图规定化和小波分析的医学图像增强[J].软件导刊,2014(4):150-151.
[4] 徐鹏飞,朱清泽.基于直方图均衡化的图像增强在医学中的应用[J].计算机产品与流通,2018(12):127.
[5] Kim T K,Paik J K,Kang B S.Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering[J].IEEE Transactions on Con-sumer Electronics,1998,44(1):82-87.
[6] Kim J Y,Kim L S,Hwang S H. An advanced contrast-enhancement using partially overlapped sub-block histo-gram equalization[J].IEEE Transactions on Circuits and Systems for Video Technology,2001,11(4):475-484.
[7] Reza A M.Realization of the contrast limited adaptive histogram equalization(CLAHE)for real-time image en-hancement[J].Journal of VLSI Signal Processing,2004,38(1):35-44.
[8] 孙忠玉.X光医学图像的降噪和增强处理研究[D].江门:五邑大学,2014.
[9] 王建,庞彦伟.基于CLAHE的X射线行李图像增强[J].天津大学学报,2010,43(3):194-198.
[10] 魏德志,梁光明.基于改进的CLAHE显微细胞图像增强算法[J].计算机技术与发展,2018,28(10):111-114.
[11] 杜欣宇,陈丽芳,刘渊.基于分块信息熵的彩色图像融合算法[J].计算机系统应用,2015(7):24-30.
[12] 徐少平,杨荣昌,刘小平.信息量加权的梯度显著度图像质量评价[J].中国图象图形学报,2014,19(2):201-210.
[13] 张小利,李雄飞,李军.融合图像质量评价指标的相关性分析及性能评估[J].自动化学报,2014,40(2):306-315.
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备注/Memo
收稿日期:2020-04-11 基金项目:四川省科技厅资助项目(2019YJ0411)