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Proceedings Paper

The image denoising technique based on independent component analysis
Author(s): Shiqun Jin; Qiaoyun Liu; Youqiang Zhong
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Paper 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.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304I (31 December 2008); doi: 10.1117/12.819722
Show Author Affiliations
Shiqun Jin, Hefei Univ. of Technology (China)
Qiaoyun Liu, Hefei Univ. of Technology (China)
Youqiang Zhong, Hefei Univ. of Technology (China)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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