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8 July 2003 Principal component analysis of noise in an image-acquisition system: bad pixel extraction
Jose Manuel Lopez-Alonso, Javier Alda
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Proceedings Volume 5036, Photonics, Devices, and Systems II; (2003) https://doi.org/10.1117/12.498343
Event: Photonics, Devices, and Systems II, 2002, Prague, Czech Republic
Abstract
The noise characterization of a set of frames can be treated by means of the principal component analysis. The main advantage of this method is that it provides a set of eigenimages that can be grouped into processes. These processes may be identified with actual sources of noise. In this scheme, bad pixels are extracted as those pixels showing an anomalous behaviour. The principal component analysis also allows to extract information about the character of the temporal evolution of the signal of the pixels. The bad pixels are identified by evaluating their place in the distribution of signal of the whole data set.
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Jose Manuel Lopez-Alonso and Javier Alda "Principal component analysis of noise in an image-acquisition system: bad pixel extraction", Proc. SPIE 5036, Photonics, Devices, and Systems II, (8 July 2003); https://doi.org/10.1117/12.498343
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KEYWORDS
Principal component analysis
Detector arrays
Sensors
Signal detection
Statistical analysis
Cameras
Image analysis
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