Naveed, Khuram and Ehsan, Shoaib and McDonald-Maier, Klaus and ur Rehman, Naveed (2019) A Multiscale Denoising Framework using Detection Theory with Application to Images from CMOS/CCD Sensors. Sensors, 19 (1). p. 206. DOI https://doi.org/10.3390/s19010206
Naveed, Khuram and Ehsan, Shoaib and McDonald-Maier, Klaus and ur Rehman, Naveed (2019) A Multiscale Denoising Framework using Detection Theory with Application to Images from CMOS/CCD Sensors. Sensors, 19 (1). p. 206. DOI https://doi.org/10.3390/s19010206
Naveed, Khuram and Ehsan, Shoaib and McDonald-Maier, Klaus and ur Rehman, Naveed (2019) A Multiscale Denoising Framework using Detection Theory with Application to Images from CMOS/CCD Sensors. Sensors, 19 (1). p. 206. DOI https://doi.org/10.3390/s19010206
Abstract
Output from imaging sensors based on CMOS and CCD devices is prone to noise due to inherent electronic fluctuations and low photon count. The resulting noise in the acquired image could be effectively modelled as signal dependent Poisson noise or as a mixture of Poisson and Gaussian noise. To that end, we propose a generalized framework based on detection theory of hypothesis testing coupled with the variance stability transformation (VST) for Poisson or Poisson-Gaussian denoising. VST transforms signal dependent Poisson noise to a signal independent Gaussian noise with stable variance. Subsequently, multiscale transforms are employed on the noisy image to segregate signal and noise into separate coefficients. That facilitates the application of local binary hypothesis testing on multiple scales using empirical distribution function (EDF) for the purpose of detection and removal of noise. We demonstrate the effectiveness of the proposed framework with different multiscale transforms and on a wide variety of input datasets.
Item Type: | Article |
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Uncontrolled Keywords: | Multiscale; Gaussian and Poisson denoising; CMOS/CCD Image Sensors; Detection 12 theory; Binary hypothesis testing; Variance stability transformation (VST) |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 08 Apr 2019 13:26 |
Last Modified: | 30 Oct 2024 20:45 |
URI: | http://repository.essex.ac.uk/id/eprint/24426 |
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Filename: A Multiscale Denoising Framework Using Detection Theory with Application to Images from CMOS/CCD Sensors.pdf
Licence: Creative Commons: Attribution 3.0