An ICA-based method for Poisson noise reduction

被引:0
|
作者
Han, XH [1 ]
Chen, YW [1 ]
Nakao, Z [1 ]
机构
[1] Univ Ryukyus, Fac Engn, Dept EEE, Nishihara, Okinawa 90301, Japan
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many image systems rely on photon detection as a basis of image formation. One of the major sources of error in these systems is Poisson noise due to the quantum nature of the photon detection process. Unlike additive Gaussian noise, Poisson noise is signal dependent, and consequently separating signal from noise is a very difficult task. In most current Poisson noise reduction algorithms, noisy signal is firstly pre-processed to approximate Gaussian noise and then denoise by a conventional Gaussian denoising algorithm. In this paper, based on the property that Poisson noise adapts to the intensity of signal, we develop and analyze a new method using an optimal ICA-domain filter for Poisson noise removal. The performance of this algorithm is assessed with simulated data experiments and experimental results demonstrate that this algorithm greatly improves the performance in denoising image.
引用
收藏
页码:1449 / 1454
页数:6
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