New disparity estimation method for multiview video based on Mean Shift

Hu, Bo; Dai, Wanchang; Xiao, Zhijian; Wu, Jianping; Hu, Jie

doi:10.3724/sp.j.1087.2013.02297

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“…Information granularity was firstly presented by Zadeh in [2] and now it has been used in rough set theory [3][4][5]. There have been many granularity models [6,7] based on rough set theory. Combining information granularity and nested sequences of equivalence relation, literature [8] given rough set approximations for information systems.…”

Section: Introductionmentioning

confidence: 99%

Interval Granules in Incomplete Information Systems

Chen

Zhang

2011

AMR

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Rough set theory is an efficient mathematical theory for data reduction and knowledge discovery of various fields. However, classical rough set theory is not applicable for knowledge induction of incomplete information systems. In this paper, a concept of interval granule is presented. Based on this concept, the hierachical structure of knowledge granularity and approximation of rough sets in incomplete information systems are studied, and related properties are given. An example show that the interval granule have better results than existing models for knowledge induction and approximation.

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