The image denoising technique based on independent component analysis
Shiqun Jin, Qiaoyun Liu, Youqiang Zhong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
In a 3D vision system with self-calibration, a new calibration method using pattern projection, it is necessary to process a lot of image data, within which the image denoising is one of the foundation work. In this paper, independent component analysis (ICA), a simple, efficient and applied method to clean image noise is introduced. Independent component analysis is a recently developed method in which the goal is to find a linear representation of non-Gaussian data so that the components are statistically independent, or as independent as possible. Such a representation seems to capture the essential structure of the data in many applications, including feature extraction and noise cleaning of an image.