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On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution

机译:通过盲反褶积补偿视网膜图像中不均匀照明的补偿

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Retinal eye fundus images are used for diagnostic purposes, but despite controlled conditions in acquisition they often suffer from uneven illumination and blur. In this work, we propose the use of multi-channel blind deconvolution for the restoration of blurred retinal images. The estimation of an adequate point-spread function (PSF) is highly dependent on the registration of at least two images from the same retina, which undergo illumination compensation. We use the bi-dimensional empirical mode decomposition (BEMD) approach to model the illumination distribution as a sum of non-stationary signals. The BEMD approach enables an artifact-free compensation of the illumination in order to estimate an adequate PSF and carry out the best restoration possible. Encouraging experimental results show significant enhancement in the retinal images with increased contrast and visibility of subtle details like small blood vessels.
机译:视网膜眼底图像用于诊断目的,但是尽管采集条件受到控制,但它们经常遭受照明不均和模糊的困扰。在这项工作中,我们建议使用多通道盲反卷积来恢复模糊的视网膜图像。适当的点扩展函数(PSF)的估计高度依赖于来自同一视网膜的至少两个图像的配准,这些图像需要进行照明补偿。我们使用二维经验模式分解(BEMD)方法将照明分布建模为非平稳信号的总和。 BEMD方法可实现对照明的无伪影补偿,以便估算适当的PSF并执行可能的最佳修复。令人鼓舞的实验结果表明,视网膜图像显着增强,对比度增强,细微细节(如小血管)的可见度也提高了。

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