期刊文献+

基于数字衍射的单幅眼底图像增强 被引量:3

Digital diffraction method for single retinal image enhancement
在线阅读 下载PDF
导出
摘要 彩色眼底图像是分析与监控眼底疾病的重要工具。由于照明不均匀的问题,眼底图像视觉质量不足,图像对比度有待提高。为此,基于数字衍射提出了一种兼顾颜色保真与亮度增强的单幅眼底图像光强校正算法。将彩色RGB眼底图像转换到LCH色彩空间进行基于L通道的光强校正,以解决眼底图像亮度的平衡问题。对C通道进行相同操作使得处理后的彩色眼底图像颜色保真性较好。在Messidor眼底图像数据集的1200组眼底图像上进行分析,并与Gamma校正、Retinex等眼底图像光强校正方法进行对比。本算法不仅具有更好的图像增强效果,改善了彩色眼底图像的颜色失真及对比度低的问题,还可进一步结合自适应直方图均衡化(CLAHE)以提升图像对比度。实验结果表明,在图像多尺度对比度和图像噪声评价指标方面优于传统算法3%~4%。经算法增强后眼底图像亮度分布更加均匀、对比度提升,为后期眼底图像病理位点的识别、血管与病灶分割和分类提供了一种性能更好的预处理方法。 Enhancing RGB retinal images is vital for retinopathy detection and monitoring,but issues like uneven intensity often degrade visual quality.This research introduces a digital diffraction-based method to improve uneven intensity and contrast while preserving color naturalness.Initially,the retinal image is converted to LCH color space,where intensity correction is applied to the L channel,treated as an optical field.A digital propagation with a specific kernel estimates the intensity pattern,which,when subtracted,yields a corrected L channel.Multi-image fusion with varied kernels then ensures uniform intensity.The same process corrects the C channel for color accuracy.Tested on 1200 Messidor dataset images,this method surpasses Gamma correction and Retinex methods,enhancing contrast and uniformity by 3%-4%when combined with CLAHE.The improved contrast aids applications like retinopathy detection and blood vessel segmentation.
作者 张书赫 曹良才 ZHANG Shuhe;CAO Liangcai(Department of Precision Instruments,Tsinghua University,Beijing 100084,China)
出处 《光学精密工程》 EI CAS CSCD 北大核心 2024年第15期2429-2438,共10页 Optics and Precision Engineering
基金 国家重点研发计划资助项目(No.2021YFB2802300)。
关键词 医学图像处理 眼底图像增强 对比度增强 数字衍射 medical image processing retinal image enhancement contrast enhancement digital diffraction
作者简介 张书赫(1994-),男,湖北武汉人,博士,助理研究员,2019年于安徽医科大学获得硕士学位,2023年于荷兰马斯特里赫特大学获得博士学位,现为清华大学精密仪器系博士后,主要从事计算光学成像及医学图像处理的研究。E-mail:shuhe-zhang@mail.tsinghua.edu.cn;通讯作者:曹良才(1977-),男,湖北公安人,博士,教授,博士生导师,主要从事光学成像与光学显示的研究。E-mail:clc@tsinghua.edu.cn。
  • 相关文献

参考文献4

二级参考文献37

  • 1徐亮,陈建华,李建军,罗灵,杨桦,张蓉秀,孙秀英,郑远远,宋维贤,施玉英,张士元,孙葆忱,赵家良,马斌荣.北京农村及城市特定人群原发性开角型青光眼的患病率调查及其筛查方法评价[J].中华眼科杂志,2004,40(11):726-732. 被引量:81
  • 2谢正祥,王志芳,刘燕欢,刘玉红,王颖,李虹.灰度谱分级平坦化理论[J].中国医学物理学杂志,2006,23(6):405-407. 被引量:19
  • 3WHO Cataract Grading Group. A simplified cataract grading system. WHO/PBL/01.81, 2002: 4-10.
  • 4Landis JR, Koch GG. The measurement of observer agreement for gategorical data. Biometrics, 1977, 33: 159-174.
  • 5Vujosevica S, Benettib E, Massignanb F, et al. Screening for diabetic retinopathy: 1 and 3 nonmydriatic 45-degree digital fundus photographs vs 7 standard early treatment diabetic retinopathy study fields. Am J Ophthalmol, 2009, 148:111-118.
  • 6Williams GA, Scott IU, Hailer JA, et al. Single-field fundus photography for diabetic retinopathy screening: a report by the American Academy of Ophthalmology. Ophthalmology, 2004, 111: 1055-1062.
  • 7Zimmer-Galler LE, Zeimer R. Feasibility of screening for high-risk age-related macular degeneration with an internet-based automated fundus camera. Ophthalmic Surg Lasers Imaging, 2005, 36: 225-236.
  • 8Parikh CH, Fowler S, Davis R. Cataract screening using telemedicine and digital fundus photography. Invest Ophthalmol Vis Sci, 2005, 46: E-Abstract 1944.
  • 9Ferraro JG, Pollard T, Muller A, et al. Detecting cataract causing visual impairment using a nonmydriatic fundus camera. Am J Ophthalmol, 2005, 139: 725-726.
  • 10Muller A, Vu HT, Ferraro JG, et al. Rapid and cost-effective method to assess vision disorders in a population. Clin Exp Ophthalmol, 2006, 34: 521-525.

共引文献49

同被引文献33

引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部