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A Novel Retinal Image Color Texture Enhancement Method Based on Multi-Regression Analysis

机译:一种基于多元回归分析的新型视网膜图像颜色纹理增强方法

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Characteristics of retinal tissue shown in retinal images are very important bases for ophthalmologists in clinical diagnosis. Among them, retinal vessel is the most important character. However, the quality of retinal image is usually poor due to the non-perfect imaging environment, making ophthalmologists difficult to read. This paper introduces a retinal vessel enhancement algorithm using multiple regression analysis (MRA) based color transformation scheme to enhance the contrast between retinal vessels and background area in retinal images. This method uses the color texture of another appropriate image as a reference to enforce color transformation on the desired target image. This paper focus on investigating the vessel enhancement effect with different reference images. The proposed method has been validated with STARE (Structure Analysis of the Retina) database. The experimental results show that, using images with lots of green and a little yellow as references can upgrade the average value of contrast to 0.2921 and 3.25 times more than the original one in STARE database. It demonstrates that the proposed method can effectively enhance the contract between retinal vessels and background area in retinal images.
机译:视网膜图像中显示的视网膜组织特征是眼科医生在临床诊断中的非常重要的基础。其中,视网膜血管是最重要的性质。然而,由于非完美的成像环境,视网膜图像的质量通常差,使眼科医生难以阅读。本文介绍了一种使用基于多元回归分析(MRA)的颜色变换方案的视网膜增强算法,以增强视网膜血管和视网膜图像背景区域之间的对比度。该方法使用另一个适当图像的颜色纹理作为引用在所需目标图像上强制执行颜色变换。本文侧重于使用不同参考图像调查血管增强效果。所提出的方法已被凝视(视网膜的结构分析)数据库验证。实验结果表明,使用具有许多绿色的图像和一点黄色作为参考可以将对比度的平均值升级到0.2921和3.25倍,而不是凝视数据库中的原始值。它表明,所提出的方法可以有效地增强视网膜血管和视网膜图像中的背景区域之间的合同。

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