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Curvelet domain image fusion of OCT and fundus imagery using convolution of Meridian distributions

机译:利用子午线分布的卷积将OCT与眼底图像进行曲波域图像融合

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This paper presents a novel statistical model based method aimed at fusing Optical Coherence Tomography and Fundus Photographic imagery of the eye. The presented method utilises the Discrete Curvelet Transform to decompose the images into sub-band coefficients. The Meridian distribution, a specialized case of the generalized Cauchy distribution, is used to model the curvelet decomposition coefficients. The convolution of the input image distributions is used as a probabilistic prior for modelling the fused image coefficients. Experimental results show this method to provide very high-quality fusion results.
机译:本文提出了一种新颖的基于统计模型的方法,旨在融合眼睛的光学相干断层扫描和眼底照相图像。提出的方法利用离散曲线波变换将图像分解为子带系数。 Meridian分布是广义Cauchy分布的一种特殊情况,用于对Curvelet分解系数进行建模。输入图像分布的卷积被用作对融合图像系数进行建模的概率先验。实验结果表明,该方法可提供非常高质量的融合结果。

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