Abstract / truncated to 115 words (read the full abstract)

Digital image acquisition is an intricate process, which is subject to various errors. Some of these errors are signal-dependent, whereas others are signal-independent. In particular, photon emission and sensing are inherently random physical processes, which in turn substantially contribute to the randomness in the output of the imaging sensor. This signal-dependent noise can be approximated through a Poisson distribution. On the other hand, there are various signal-independent noise sources involved in the image capturing chain, arising from the physical properties and imperfections of the imaging hardware. The noise attributed to these sources is typically modelled collectively as additive white Gaussian noise. Hence, we have three common ways of modelling the noise present in a digital ... toggle 10 keywords

digital imaging denoising poisson noise poisson-gaussian noise signal-dependent noise variance stabilization VST anscombe inverse transformation unbiased


Mäkitalo, Markku
Tampere University of Technology
Publication Year
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March 2, 2014

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