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Enhancement of fundus imagery

机译:眼底图像的增强

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摘要

Diabetic Retinopathy (DR) is usually diagnosed and graded based on the incidence and severity of micro-aneurysms, hemorrhages, macular/retinal edema andexudates on the fundus images. Similarly, optical Cup to Disc Ratio (CDR) is another feature based on which the progression of glaucoma is evaluated. To enable easy identification of these clinical indications from the fundus images, their contrast has to be improved to appreciable level. Contrast Limited Adaptive Histogram Equalization (CLAHE) is one of the widely accepted contrast enhancement scheme for fundus images. But, in CLAHE, the contrast and quality of the enhanced image heavily relies on the colour model used to represent the contextual image, the channel/component subjected to equalization and the shape of the specified histogram. This article investigate the colour model, adequate channel to be equalized and the histogram specification which offer maximum grey level contrast and image quality in fundus images, when enhanced with CLAHE. It has been observed that RGB model outperforms HSV model, the adequate channel to be equalized is the green and exponential histogram is the apt choice for fundus imagery. The experimental analysis is performed in Matlab®.
机译:通常根据眼底图像上微动脉瘤,出血,黄斑/视网膜水肿和渗出液的发生率和严重程度对糖尿病性视网膜病(DR)进行诊断和分级。类似地,光学杯对椎间盘比率(CDR)是另一种功能,可据此评估青光眼的进展。为了能够从眼底图像中轻松识别这些临床指征,必须将其对比度提高到可观的水平。对比度受限的自适应直方图均衡化(CLAHE)是眼底图像被广泛接受的对比度增强方案之一。但是,在CLAHE中,增强图像的对比度和质量很大程度上取决于用于表示上下文图像的颜色模型,经过均衡处理的通道/分量以及指定直方图的形状。本文研究了使用CLAHE增强后的色彩模型,足够的通道均衡性和直方图规范,这些规范可提供眼底图像中最大的灰度对比度和图像质量。已经观察到,RGB模型优于HSV模型,要均衡的足够通道是绿色,指数直方图是眼底图像的合适选择。实验分析在Matlab®中进行。

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