Feedback particle filter based image denoiser

Harish Kumar, A. Mishra
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引用次数: 5

Abstract

This paper presents a new approach for imagedenoising using feedback particle filter (FPF). The feedback structure is decisive factor of FPF and is based on innovation error. To improve system's performance by minimizing mean square error and selection of number of particles are analyzedand experimental analysis for different parameters are compared with conventional non-linear particle filter. In FPF the gain and innovation error depends on values of variance and mean of particles, hence it is generated in dynamic manner. The feedback particle filter gives better result than non-linear particle filter. This paper concludes that FPF image denoiser can very well applicable in the field of image enhancement.
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基于反馈粒子滤波的图像去噪
提出了一种利用反馈粒子滤波(FPF)进行图像去噪的新方法。反馈结构是FPF的决定性因素,是基于创新误差的。为了通过最小化均方误差和粒子数的选择来提高系统的性能,并对不同参数下的实验结果与传统的非线性粒子滤波进行了比较。在FPF中,增益和创新误差取决于粒子的方差和均值,因此是动态产生的。反馈粒子滤波比非线性粒子滤波效果更好。结果表明,FPF图像去噪算法在图像增强领域具有很好的应用前景。
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