Blind Separation of Images using Temporal Predictability

In this study, the linear and kernelized temporal predictability methods which have been used to separate audio mixtures have been applied to blind source separation of linear and nonlinear image mixtures and the statistical performance of the algorithms have been simulated using different algorithm parameters like kernel degree, kernel type, image mass size and nonlinear mixing function. The data sets are chosen to simulate the effect or corruption of images with writing or scribbles.