Denoising Methods for Retinal Fundus Images

被引：0

作者：

Hani, Ahmad Fadzil M. ^{[1
]}

Soomro, Toufique Ahmed ^{[1
]}

Faye, Ibrahima ^{[1
]}

Kamel, Nidal ^{[1
]}

Yahya, Norashikin ^{[1
]}

机构：

[1] Univ Teknol PETRONAS, Dept Elect & Elect Engn, Ctr Intelligent Signal & Imaging Res CISIR, Tronoh 31750, Malaysia

来源：

2014 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT AND ADVANCED SYSTEMS (ICIAS 2014) | 2014年

关键词：

Noise reduction; Retinal fundus images; PSNR; linear sub-space time domain constraint estimator;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Diagnosing retinal diseases of the eye requires analysing tiny retinal vessels. Digital colour fundus images are plagued by the problem of low and varied contrast. Further, with noise being present in the images, retinal vasculature is difficult to be analysed. This paper discusses various denoising methods to improve the SNR of the retinal fundus images before further image enhancement. By selecting a suitable method for denoising, the image's details are not lost as well as the contrast is maintained. Based on the performance of several techniques for denoising fundus images, it was found that the Time Domain Constraint Estimator (TDCE) showed a greater performance in the PSNR improvement of retinal fundus images. By reducing noise using TDCE, the performance of non-invasive methods for enhancing fundus images can be significantly improved without any loss of the details of the images.

引用

页数：6

共 16 条

[1]

Ahmad Fadzil T. A. S., 2013, IEEE INT C CONTR SYS

[2]

Aja-Fernandez Santiago, 2006, Conf Proc IEEE Eng Med Biol Soc, V2006, P4815

[3]

[Anonymous], 1998, FLUORESCEIN ICG ANGI

[4] DE-NOISING BY SOFT-THRESHOLDING [J].