Image Denoising With Gaussian Mixture Model

2008 ◽  
Author(s):  
Yang Cao ◽  
Yupin Luo ◽  
Shiyuan Yang
Keyword(s):  
Image Denoising ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture

scholarly journals Image Denoising Based on Improved Gaussian Mixture Model

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hui Wei ◽  
Wei Zheng
Keyword(s):  
Mixture Models ◽  
Image Denoising ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Denoising Method ◽  
L2 Norm ◽  
Image Area ◽  
The Difference

An image denoising method is proposed based on the improved Gaussian mixture model to reduce the noises and enhance the image quality. Unlike the traditional image denoising methods, the proposed method models the pixel information in the neighborhood around each pixel in the image. The Gaussian mixture model is employed to measure the similarity between pixels by calculating the L2 norm between the Gaussian mixture models corresponding to the two pixels. The Gaussian mixture model can model the statistical information such as the mean and variance of the pixel information in the image area. The L2 norm between the two Gaussian mixture models represents the difference in the local grayscale intensity and the richness of the details of the pixel information around the two pixels. In this sense, the L2 norm between Gaussian mixture models can more accurately measure the similarity between pixels. The experimental results show that the proposed method can improve the denoising performance of the images while retaining the detailed information of the image.

scholarly journals Image Denoising with Generalized Gaussian Mixture Model Patch Priors

2018 ◽  
Vol 11 (4) ◽  
pp. 2568-2609 ◽  
Author(s):  
Charles-Alban Deledalle ◽  
Shibin Parameswaran ◽  
Truong Q. Nguyen
Keyword(s):  
Image Denoising ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture
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