The image denoising technique based on independent component analysis

Shiqun Jin; Qiaoyun Liu; Youqiang Zhong

doi:10.1117/12.819722

31 December 2008 The image denoising technique based on independent component analysis

Shiqun Jin, Qiaoyun Liu, Youqiang Zhong

Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71304I (2008) https://doi.org/10.1117/12.819722
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China

Abstract

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.

Citation Download Citation

Shiqun Jin, Qiaoyun Liu, and Youqiang Zhong "The image denoising technique based on independent component analysis", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304I (31 December 2008); https://doi.org/10.1117/12.819722

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