Robust single image noise estimation from approximate local statistics
- Roodt, Yuko, Clarke, Wimpie, Robinson, Philip E., Nel, André
- Authors: Roodt, Yuko , Clarke, Wimpie , Robinson, Philip E. , Nel, André
- Date: 2012
- Subjects: Gaussian noise , Imaging sensors
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/16706 , uj:15802 , Roodt, Y., Robinson, P.E. & Nel, A. Robust single image noise estimation from approximate local statistics. Proceedings of the Twenty-Third Annual Symposium of the Pattern Recognition Association of South Africa, November 2012, pp 47-53.
- Description: Abstract: A novel method for estimating the variance and standard deviation of the additive white Gaussian noise contained in an image will be presented. Only a single image is used to estimate the noise properties. Local image outliers are discarded, this allows us to separate the additive zero mean white Gaussian noise contained in a noisy image from the original image structure. Local variance estimates can then be calculated from the extracted noise. These local variance estimates are weak and can be influenced by misclassified image information. Robust statistics are then used to fuse the weak local variance estimates to obtain a robust global noise variance estimate. This method of estimating the noise properties is computationally efficient and provides reliable estimation results in synthetic and real-world imagery. The accuracy and processing complexity of the proposed algorithm will be compared against the current state-of-the-art noise estimators.
- Full Text:
- Authors: Roodt, Yuko , Clarke, Wimpie , Robinson, Philip E. , Nel, André
- Date: 2012
- Subjects: Gaussian noise , Imaging sensors
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/16706 , uj:15802 , Roodt, Y., Robinson, P.E. & Nel, A. Robust single image noise estimation from approximate local statistics. Proceedings of the Twenty-Third Annual Symposium of the Pattern Recognition Association of South Africa, November 2012, pp 47-53.
- Description: Abstract: A novel method for estimating the variance and standard deviation of the additive white Gaussian noise contained in an image will be presented. Only a single image is used to estimate the noise properties. Local image outliers are discarded, this allows us to separate the additive zero mean white Gaussian noise contained in a noisy image from the original image structure. Local variance estimates can then be calculated from the extracted noise. These local variance estimates are weak and can be influenced by misclassified image information. Robust statistics are then used to fuse the weak local variance estimates to obtain a robust global noise variance estimate. This method of estimating the noise properties is computationally efficient and provides reliable estimation results in synthetic and real-world imagery. The accuracy and processing complexity of the proposed algorithm will be compared against the current state-of-the-art noise estimators.
- Full Text:
Blind deconvolution of Gaussian blurred images containing additive white Gaussian noise
- Robinson, Philip E., Roodt, Yuko
- Authors: Robinson, Philip E. , Roodt, Yuko
- Date: 2013
- Subjects: Gaussian blur , Gaussian noise , Bind deconvolution
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/16753 , uj:15807 , Robinson, P.E. & Roodt, Y. Blind deconvolution of Gaussian blurred images containing additive white Gaussian noise. IEEE International Conference on Industrial Technology (ICIT 2013), 2013, pp. 1092-1097.
- Description: Abstract: Image restoration algorithms are used to reconstruct the information that is suppressed when an observed image is subjected to blurring. These algorithms generally assume that knowledge of the nature of the distortion and noise contained in an observed image is available. When this information is not available and has to be directly estimated from the image being processed the problem becomes one of blind deconvolution. This paper makes use of a novel blur identification technique and a noise identification technique to perform blind deconvolution on single images that have been degraded by a Gaussian blur and contain additive white Gaussian noise.
- Full Text:
- Authors: Robinson, Philip E. , Roodt, Yuko
- Date: 2013
- Subjects: Gaussian blur , Gaussian noise , Bind deconvolution
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/16753 , uj:15807 , Robinson, P.E. & Roodt, Y. Blind deconvolution of Gaussian blurred images containing additive white Gaussian noise. IEEE International Conference on Industrial Technology (ICIT 2013), 2013, pp. 1092-1097.
- Description: Abstract: Image restoration algorithms are used to reconstruct the information that is suppressed when an observed image is subjected to blurring. These algorithms generally assume that knowledge of the nature of the distortion and noise contained in an observed image is available. When this information is not available and has to be directly estimated from the image being processed the problem becomes one of blind deconvolution. This paper makes use of a novel blur identification technique and a noise identification technique to perform blind deconvolution on single images that have been degraded by a Gaussian blur and contain additive white Gaussian noise.
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