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

A. Marrugo, Raul Vargas, S. Contreras, M. S. Millán
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引用次数: 1

Abstract

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.
用盲反卷积法补偿视网膜图像中光照不均匀的恢复
视网膜眼底图像用于诊断目的,但尽管在采集时控制条件,但它们经常受到光照不均匀和模糊的影响。在这项工作中,我们提出使用多通道盲反卷积来恢复模糊的视网膜图像。一个适当的点扩散函数(PSF)的估计高度依赖于至少两个图像的配准从同一视网膜,其中进行照明补偿。我们使用二维经验模态分解(BEMD)方法将光照分布建模为非平稳信号的和。BEMD方法能够对照明进行无伪影补偿,以便估计足够的PSF并进行最佳恢复。令人鼓舞的实验结果显示,视网膜图像的对比度和细微细节(如小血管)的可见性显著增强。
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