Exact Unbiased Inverse of the Anscombe Transformation and its Poisson-Gaussian Generalization (2013)
Abstract / truncated to 115 words
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 ...
digital imaging – denoising – poisson noise – poisson-gaussian noise – signal-dependent noise – variance stabilization – VST – anscombe – inverse transformation – unbiased
Information
- Author
- Mäkitalo, Markku
- Institution
- Tampere University of Technology
- Supervisor
- Publication Year
- 2013
- Upload Date
- March 2, 2014
First few pages / click to enlarge
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.