Non-Linear Image Fusion Using Variational Osmosis PROJECT TITLE : Variational Osmosis for Non-Linear Image Fusion ABSTRACT: Non-linear image fusion can be improved by using a novel variational model proposed by us. Osmosis energy terms that are similar to those explored in Vogel et al. and Weicker et et. The proposed non-convex energy minimization achieves visually realistic picture data fusion, which is invariant to multiplicative brightness variations. However, it can encode information about the structure of pictures to be fused and requires little supervision and parameter modification in practise. It is proposed that we build a primal-dual method and apply it to solve multi-modal face fusion, colour transfer, and cultural heritage conservation issues numerically using the resulting minimization scheme. Comparisons to current methods show that our method outperforms and is more flexible than current methods. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Color Deconvolution of Histopathological Images Using Variational Bayesian Blind Color Deconvolution Unsupervised Domain Adaptation Visual Correspondences on Electron Microscopy Images
