Noise parameter estimation for poisson corrupted images using variance stabilization transforms.
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.
Xiaodan
X
Jin
Zhenyu
Z
Xu
Keigo
K
Hirakawa
D000465:Algorithms; D016477:Artifacts; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016012:Poisson Distribution; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio