Fast mean shift based traffic image filtering algorithm

Zhang Yu, Shi Zhong-ke, Wang Run-quan
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引用次数: 3

Abstract

This paper describes a novel fast mean shift algorithm based on an accelerated iteration strategy. This new method focuses on solving the problem of high calculation complexity when high data dimension or large data sets are involved in mean shift. By predicting the mean shift vector, improved method reduces the number of iteration and speed up the calculation. The application of traffic image filtering is provided also. Experiment results of traffic image filtering demonstrate the efficiency of the fast mean shift algorithm.
基于均值移位的快速交通图像滤波算法
提出了一种基于加速迭代策略的快速均值移位算法。该方法主要解决了高数据维数或大数据集的均值移位问题。改进方法通过预测平均位移向量,减少了迭代次数,提高了计算速度。并给出了交通图像滤波的应用。交通图像滤波实验结果验证了快速均值移位算法的有效性。
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