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Noise Parameter Estimation for Poisson Corrupted Images Using Variance Stabilization Transforms

delete2014-03-01
delete21
PRE
AI
X
Xiaodan Jin *
Z
Zhenyu Xu
K
Keigo Hirakawa
DOI:10.1109/TIP.2014.2300813delete
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摘要

摘要

En 中文
Noise is present in all images captured by real-world image sensors. Poisson distribution is said to model the stochastic nature of the photon arrival process and agrees with the distribution of measured pixel values. We propose a method for estimating unknown noise parameters from Poisson corrupted images using properties of variance stabilization. With a significantly lower computational complexity and improved stability, the proposed estimation technique yields noise parameters that are comparable in accuracy to the state-of-art methods.
Keyword:
Image denoising
noise parameter estimation
Poisson
variance stabilization
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期刊

IEEE Transactions on Image Processing 封面图
IEEE Transactions on Image Processing
IF:
13.7
论文数:
1.0W
被引数:
8.4W

机构

U
University System of Ohio
学者数:
15.5W
论文数: 13.0W
被引数: 200
U
university of dayton
学者数:
21
论文数: 15
被引数: 0
H
Harvard University
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1.4K
论文数: 548
被引数: 0
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引用论文

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