Enhancement and Assessment of the Fundus Image_Journal of Biomedical Engineering

Authors：

CHENMengmeng ,  XIONGXingliang , LIGuang , ZHANGTingting

Department of Biomedical Engineering, Chongqing Medical University, Chongqing 400016, China;

Corresponding author：

XIONGXingliang, Email: xxlsober@sina.com

Keywords：

top-hat transform; contrast limited adaptive histogram equalization; image contrast; image quality assessment

DOI：

10.7507/1001-5515.20140216

Video：

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Abstract Full text Figures/Tables Video References Cited by

A new enhancement method is proposed based on the characteristics of fundus images in this paper. Firstly, top-hat transform is utilized to weaken the background. Secondly, contrast limited adaptive histogram equalization (CLAHE) is performed to improve the uneven illumination. Finally, two-dimensional matched filters are designed to further enhance the contrast between blood vessels and background. The algorithm was tested in DIARETDB0 databases and showed good applicability for both normal and pathological fundus images. A new no-reference image quality assessment method was used to evaluate the enhancement methods objectively. The results demonstrated that the proposed method could effectively weaken the background, increase contrast, enhance details in the fundus images and improve the image quality greatly.

Citation： CHENMengmeng, XIONGXingliang, LIGuang, ZHANGTingting. Enhancement and Assessment of the Fundus Image. Journal of Biomedical Engineering, 2014, 31(5): 1144-1148. doi: 10.7507/1001-5515.20140216 Copy

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12.	REZA A M. Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement[J]. Journal of VLSI Signal Processing, 2004, 8(1): 35-44.
13.	BENITEZ-GARCIA G, OLIVARES-MERCADO J, AGUILAR-TORRES G, et al. Face identification based on contrast limited adaptive histogram equalization (CLAHE)[C]//Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'11), WORLDCOMP. 11. Los Vegas: 2011.
14.	CHAUDHURI S, CHATTERJEE S, KATZ N, et al. Detection of blood vessels in retinal images using two-dimensional matched filters[J]. IEEE Trans Med Imaging, 1989, 8(3): 263-269.
15.	高新波,路文.视觉信息质量评价方法[M].西安:西安电子科技大学出版社,2011:2-6.
16.	谢正祥, 王志芳, 熊兴良, 等. 基于视觉感知噪声模型的彩色图像质量评价和彩色图像质量最佳化[J]. 中国图象图形学报A,2010, 15(10): 1454-1464.

1. PATTON N, ASLAM T M, MACGILLIVRAY T, et al. Retinal image analysis: concepts, applications and potential[J]. Prog Retin Eye Res, 2006, 25(1): 99-127.
2. POLI R, VALLI G. An algorithm for real-time vessel enhancement and detection[J]. Comput Methods Programs Biomed, 1997, 52(1): 1-22.
3. LIN T, ZHENG Y. Adaptive image enhancement for retinal blood vessel segmentation[J]. Electron Lett, 2002, 38(19):1090-1091.
4. AL-RAWI M, QUTAISHAT M, ARRAR M. An improved matched filter for blood vessel detection of digital retinal images[J]. Comput Biol Med, 2007, 37(2): 262-267.
5. FENG P, PAN Y, WEI B, et al. Enhancing retinal image by the contourlet transform[J]. Pattern Recognit Lett, 2007, 28(4): 516-522.
6. CHEN J, TIE J, TANG Z, et al. Retinal vessel enhancement and extraction based on directional field[J]. J X-Ray Sci Technol, 2008, 16(3): 189-201.
7. JOSHI G D, SIVASWAMY J. Colour retinal image enhancement based on domain knowledge[C]//Proceedings of the 6th Indian Conference on Computer Vision/Graphics & Image Processing. Bhubaneswar: 2008:591-598.
8. 章毓晋.图像工程(中册)图像分析[M].北京:清华大学出版社,2005:413-417.
9. 张文超,王岩飞,陈贺新.基于Tophat变换的复杂背景下运动点目标识别算法[J].中国图象图形学报,2007,12(5):871-874.
10. PISANO E D, ZONG S, HEMMINGER B M, et al. Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms[J]. J Digit Imaging, 1998, 11(4): 193-200.
11. CROMARTIE R, PIZER S M. Edge-affected context for adaptive contrast enhancement[C]//Information Processing in Medical Imaging/Springer,Berlin:1991: 474-485.
12. REZA A M. Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement[J]. Journal of VLSI Signal Processing, 2004, 8(1): 35-44.
13. BENITEZ-GARCIA G, OLIVARES-MERCADO J, AGUILAR-TORRES G, et al. Face identification based on contrast limited adaptive histogram equalization (CLAHE)[C]//Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'11), WORLDCOMP. 11. Los Vegas: 2011.
14. CHAUDHURI S, CHATTERJEE S, KATZ N, et al. Detection of blood vessels in retinal images using two-dimensional matched filters[J]. IEEE Trans Med Imaging, 1989, 8(3): 263-269.
15. 高新波,路文.视觉信息质量评价方法[M].西安:西安电子科技大学出版社,2011:2-6.
16. 谢正祥, 王志芳, 熊兴良, 等. 基于视觉感知噪声模型的彩色图像质量评价和彩色图像质量最佳化[J]. 中国图象图形学报A,2010, 15(10): 1454-1464.

Journal of Biomedical Engineering

Enhancement and Assessment of the Fundus Image

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