7 March 2014 Image sensor noise profiling by voting based curve fitting
Author Affiliations +
The output quality of an image filter for reducing noise without damaging the underlying signal, strongly depends on the accuracy of the noise model in characterizing the noise introduced by the acquisition device. In this paper we provide a solution for characterizing signal dependent noise injected at shot time by the image sensor. Different fitting models describing the behavior of noise samples are analyzed, with the aim of finding a model that offers the most accurate coverage of the sensor noise under any of its operating conditions. The noise fitting equation minimizing the residual error is then identified. Moreover, a novel algorithm able to obtain the noise profile of a generic image sensor without the need of a controlled environment is proposed. Starting from a set of heterogeneous CFA images, by using a voting based estimator, the parameters of the noise model are estimated.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Battiato, S. Battiato, G. Puglisi, G. Puglisi, R. Rizzo, R. Rizzo, A. Bosco, A. Bosco, A. R. Bruna, A. R. Bruna, "Image sensor noise profiling by voting based curve fitting", Proc. SPIE 9023, Digital Photography X, 90230M (7 March 2014); doi: 10.1117/12.2038239; https://doi.org/10.1117/12.2038239


Multiresolution example-based depth image restoration
Proceedings of SPIE (September 02 2009)
Adaptive automatic terrain extraction
Proceedings of SPIE (August 04 1997)
Noise reduction techniques for Bayer-matrix images
Proceedings of SPIE (April 23 2002)
Process simulation in digital camera system
Proceedings of SPIE (May 01 2012)
Latent and apparent image quality metrics
Proceedings of SPIE (July 29 2002)

Back to Top