A trained motion adaptive temporal filter based on proportional-integral-derivative temporal classification

K. Lim, S. D. Kim
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Abstract

A classification-based trained motion adaptive temporal filtering scheme was proposed. The proposed method calculates class code and assigns optimal temporal filter coefficients based on pixel-wise temporal movement. The proportional-integral-derivative (PID) control concept was newly applied to enhance classifier. The proposed method involves integral and derivative terms of temporal movement as well as conventional proportional term. Simulation results show that significant improvement was achieved with new classification method.
基于比例-积分-导数时间分类的训练运动自适应时间滤波器
提出了一种基于分类的训练运动自适应时域滤波方案。该方法计算类代码,并根据逐像素的时间运动分配最佳的时间滤波器系数。将比例-积分-导数(PID)控制概念应用于分类器的增强。该方法包括时间运动的积分项和导数项以及传统的比例项。仿真结果表明,新分类方法的有效性得到了显著提高。
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