PP/PSWavefield separation by independent component analysis

Separation of Reflection Components by Kernel Independent Component Analysis

When we view a scene through transparent glass, the image is a linear superposition of two images, a real image observed through a glass and a virtual image reflected on it. We can separate the reflections by a polarization and Independent Component Analysis (ICA). Since the image observed through digital camera is non-linearly transformed by gamma correction etc, it may cause error in image pr...

Independent component analysis and blind source separation

Independent Component Analysis and Blind Source Separation

Blind source separation and independent component analysis

This special issue of Neurocomputing contains a selection of eleven papers about blind source separation and independent component analysis. The papers represent improved and extended versions of contributed papers presented at the ICA 2004 meeting held in Granada, Spain. A total of 15 manuscripts have been suggested for the special issue by the referees of the contributions submitted to the co...

​Rank based Least-squares Independent Component Analysis

  In this paper, we propose a nonparametric rank-based alternative to the least-squares independent component analysis algorithm developed. The basic idea is to estimate the squared-loss mutual information, which used as the objective function of the algorithm, based on its copula density version. Therefore, no marginal densities have to be estimated. We provide empirical evaluation of th...