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唐权华1, 雷金娥2, 周 艳3, 金炜东3(1.西南交通大学信息科学与技术学院,成都 610031;2.南昌工程学院计算机科学系,南昌 330099;3.西南交通大学电气工程学院,成都 610031)

摘 要
Multi-scale Space Compressed Measure-integral Based Median Computation

TANG Quanhua1, LEI Jine2, ZHOU Yan3, JIN Weidong3(1.School of Information Science & Technology, South.west Jiaotong University, Chengdu 610031;2.School of Computer Science, Nanchang Institute of Technology,Nanchang 330099;3.School of Electrical Engineering, South.west Jiaotong University, Chengdu 610031)

Due to its effectiveness for removing impulse noise and preserving detail features, median filtering has long been a popular tool of filtering algorithm. But in practice, an important issue of applying median filtering is the filtering speed. In this paper, a fast median algorithm based on measure-integral is proposed. A step function is employed to expand the array for median, then the relationship between median and measure-integral is deduced and an algorithm is gained by it. To the question that the compute time of the algorithm increases rapidly when the values of the array or the function range become large, a method of compress the measure space is put forward, which is extended to multi-scale compress method at last. Experiments show that multi-scale space compressed measure-integral based median computation(MCMIM) has higher processing speed and can be combined with most of the earlier improved median filters.