CurvatureFilter

These curvature filters were developed by Yuanhao Gong during his PhD studies. MC filter and TV filter are exactly the same as described in the paper. However, the GC filter is slightly modified. Please cite the following papers if you use a curvature filter in your work. Traditional solvers, such as gradient descent or Euler Lagrange Euqation, start at the total energy and use diffusion scheme to carry out the minimization. When the initial condition is the original image, the data fitting energy always increases while the regularization energy always reduces during the optimization. Thus, regularization energy must be the dominant part since the total energy has to decrease. Therefore, Curvature filters focus on minimizing the regularization term, whose minimizers are already known. For example, if the regularization is Gaussian curvature, the developable surfaces minimize this energy.