Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
-
Upload
leah-parker -
Category
Documents
-
view
61 -
download
0
description
Transcript of Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
![Page 1: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/1.jpg)
Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-
Image Raw-DataReporter:沈廷翰 陳奇業
![Page 2: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/2.jpg)
Poissonian-Gaussian Modeling
• : the pixel position in the domain X• : the recorded signal• : the ideal signal• : zero-mean independent random noise with
standard deviation equal to 1• : function of that gives the standard deviation
of the overall noise component
![Page 3: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/3.jpg)
Poissonian-Gaussian Modeling
![Page 4: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/4.jpg)
Poissonian-Gaussian Modeling
• : Poissonian signal-dependent component– the Poissonian has varying variance that
depends on the value of– ,
• : Gaussian signal-independent component– constant variance equal to
![Page 5: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/5.jpg)
The Algorithm
• Our goal is to estimate the function of the observation model from a noisy image
• local estimation of multiple expectation/ standard-deviation pairs
• global parametric model fitting to these local estimates– Maximum-Likelihood Fitting of a Global
Parametric Model
![Page 6: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/6.jpg)
The Algorithm
![Page 7: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/7.jpg)
Poissonian-Gaussian Modeling
• Wavelet approximation , restricted on the set of smoothness
![Page 8: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/8.jpg)
Poissonian-Gaussian Modeling
• detail coefficients , restricted on the set of smoothness
![Page 9: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/9.jpg)
Poissonian-Gaussian Modeling
• two level-sets , • : allowed deviation
![Page 10: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/10.jpg)
Poissonian-Gaussian Modeling
![Page 11: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/11.jpg)
Poissonian-Gaussian Modeling
• Two segments S obtained for = 0.01 (left) and = 0.0001(right).
• The value of is the same for both segments
![Page 12: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/12.jpg)
The Algorithm
• The solid line shows the maximum-likelihood estimate of the true standard-deviation function
• Estimates the parameters of the noise
![Page 13: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/13.jpg)
The Algorithm
• posterior likelihood
![Page 14: Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data](https://reader035.fdocuments.net/reader035/viewer/2022062221/56812b07550346895d8ee983/html5/thumbnails/14.jpg)
Conclusion
• Utilizes a special ML fitting of the parametric model on a collection of local wavelet-domain estimates of mean and standard-deviation