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Sensors 2019, 19(1), 206; https://doi.org/10.3390/s19010206

A Multiscale Denoising Framework Using Detection Theory with Application to Images from CMOS/CCD Sensors

1
Department of Electrical and Computer Engineering, COMSATS University, Park Road, Islamabad 45550, Pakistan
2
School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK
*
Author to whom correspondence should be addressed.
Received: 14 November 2018 / Revised: 13 December 2018 / Accepted: 18 December 2018 / Published: 8 January 2019
(This article belongs to the Section Physical Sensors)
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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 and 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. View Full-Text
Keywords: multiscale; Gaussian and Poisson denoising; CMOS/CCD image sensors; detection theory; binary hypothesis testing; variance stability transformation (VST) multiscale; Gaussian and Poisson denoising; CMOS/CCD image sensors; detection theory; binary hypothesis testing; variance stability transformation (VST)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Naveed, K.; Ehsan, S.; McDonald-Maier, K.D.; Ur Rehman, N. A Multiscale Denoising Framework Using Detection Theory with Application to Images from CMOS/CCD Sensors. Sensors 2019, 19, 206.

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