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

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.