Translator Disclaimer
Paper
9 May 2011 Removing ths statistical bias from three-dimensional noise measurements
Author Affiliations +
Abstract
The three dimensional noise model (3D noise) is a widely used model for characterizing noise in thermal imaging system. In this model, a sequence of images of a uniform background are acquired, and organized in a three dimensional matrix. This matrix is then decomposed into eight orthogonal noise components that can be assessed individually to yield an understanding about the magnitude and source of noise in a given system. In a previous paper we showed that the operators used to estimate the magnitude of the 3D noise in a system are biased statistical estimators that lead to systematic errors when measuring system noise. Here we provide new definitions for the noise estimators that enable removal of the statistical bias, and accurate estimation of system noise using the 3D noise model.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ze'ev Bomzon "Removing ths statistical bias from three-dimensional noise measurements", Proc. SPIE 8014, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXII, 801416 (9 May 2011); https://doi.org/10.1117/12.884469
PROCEEDINGS
9 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT

3D medical thermography device
Proceedings of SPIE (May 12 2015)
Quantitative vertebral morphometry in 3D
Proceedings of SPIE (March 13 2013)
Biases in the estimation of 3D noise in thermal imagers
Proceedings of SPIE (October 28 2010)
A measurement error evaluation method of videometrics
Proceedings of SPIE (August 18 2011)

Back to Top