A variational approach to denoising problem

Q4 Computer Science
D. Thanh
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引用次数: 0

Abstract

A digital image can be created by different digital devices, such as digital cameras, X-ray scanners, etc. In practice, such devices can give unexpected defects, for example, noise. The Gaussian noise and Poisson noise are very important, but their combination is important too. This mixed noise usually appears in electronic microscopic images, in aerospace images, etc. Our goal is to combine ROF model (for Gaussian noise removal) and modified ROF model (for Poisson noise removal) to create new model that can treat this combination effectively. Our model will treat this combination with considering proportion of noise between them.
去噪问题的变分方法
数字图像可以由不同的数字设备生成,如数码相机、x射线扫描仪等。在实践中,这样的装置可能会产生意想不到的缺陷,例如噪音。高斯噪声和泊松噪声是非常重要的,但它们的组合也很重要。这种混合噪声通常出现在电子显微图像、航空航天图像等。我们的目标是将ROF模型(用于高斯噪声去除)和改进的ROF模型(用于泊松噪声去除)结合起来,创建可以有效处理这种组合的新模型。我们的模型将通过考虑它们之间的噪声比例来处理这种组合。
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来源期刊
Electronic Letters on Computer Vision and Image Analysis
Electronic Letters on Computer Vision and Image Analysis Computer Science-Computer Vision and Pattern Recognition
CiteScore
2.50
自引率
0.00%
发文量
19
审稿时长
12 weeks
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