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Observation model based retinal fundus image normalization and enhancement

机译:基于观察模型的视网膜眼底图像归一化与增强

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Based on an observation model, a method to normalize non-uniformly luminosity and contrast present in retinal funds images is proposed. By sub-sampling and interpolation techniques, the background of the retinal images can be estimated. On this basis, the details of the image will be enhanced by singular value processing and homomorphic filtering techniques. Experiment results show that this method can effectively achieve non-uniform illumination and contrast normalization and image contrast enhancement, which meet the requirements of retinal image preprocessing. Moreover, subjective visual observation and objective evaluation test show that this method is significantly better than many other similar methods.
机译:提出了一种基于观测模型的视网膜资金图像中不均匀亮度和对比度进行归一化的方法。通过子采样和内插技术,可以估计视网膜图像的背景。在此基础上,将通过奇异值处理和同态滤波技术来增强图像的细节。实验结果表明,该方法可以有效地实现照明不均匀,对比度归一化和图像对比度增强,满足视网膜图像预处理的要求。此外,主观视觉观察和客观评估测试表明,该方法明显优于许多其他类似方法。

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