| Adaptive deinterlacing algorithm based on motion compensation |
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| 引用本文： | Gao Xinbo1 & Gu Junxia21. School of Electronic Engineering,Xidian Univ.,Xi''''an 710071,P. R. China,2. Dept. of Electronic Engineering,Tsinghua Univ.,Beijing 100084,P. R. China. Adaptive deinterlacing algorithm based on motion compensation[J]. 系统工程与电子技术(英文版), 2005, 16(4) |
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| 作者姓名： | Gao Xinbo1 & Gu Junxia21. School of Electronic Engineering Xidian Univ. Xi''''an 710071 P. R. China 2. Dept. of Electronic Engineering Tsinghua Univ. Beijing 100084 P. R. China |
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| 作者单位： | Gao Xinbo1 & Gu Junxia21. School of Electronic Engineering，Xidian Univ.，Xi'an 710071，P. R. China;2. Dept. of Electronic Engineering，Tsinghua Univ.，Beijing 100084，P. R. China |
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| 基金项目： | ThisprojectwassupportedbytheNationalNaturalScienceFoundationofChina(60202004)andtheKeyProjectofChineseMinistryofEducation(104173). |
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| 摘 要： | Keywords:de interlace,adaptivemotionestimation,Kalmanfilter,motioncompensation.1.INTRODUCTION Inthecurrentworldwidetelevisionsystems,inter lacedscanningtechniqueisadoptedtoreducethe bandwidthofthevideosignals.Butamajordrawback oftheinterlacingonthecurrentbrighthigh resolu tiondisplaysisthelineflickerandjaggedeffectsof movingedges.Thus,manyde interlacingalgorithms havebeenproposedtoreducethoseartifacts.Theex istingalgorithmscanbeclassifiedintointra field,and inter fieldtechniques[1].Intra…
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Adaptive de-interlacing algorithm based on motion compensation |
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| Gao Xinbo,Gu Junxia. Adaptive de-interlacing algorithm based on motion compensation[J]. Journal of Systems Engineering and Electronics, 2005, 16(4) |
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| Authors: | Gao Xinbo Gu Junxia |
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| Affiliation: | 1. School of Electronic Engineering, Xidian Univ., Xi'an 710071, P. R. China
2. Dept. of Electronic Engineering, Tsinghua Univ., Beijing 100084, P. R. China |
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| Abstract: | An adaptive deinterlacing algorithm based on motion compensation is presented. It consists of the detection of motion blocks, the adaptive motion estimation with Kalman filtering, and the motion compensation for motion blocks and field repetition for static blocks. The detection of motion blocks can accurately identify the motion blocks by using successive 4field images. The motion estimation module with Kalman filtering searches motion vectors only for motion blocks, and the search model is adaptive to motion velocity and acceleration. Two deinterlacing methods are adopted to satisfy the different requirements of motion blocks and static blocks. Compared with full search algorithm, the proposed algorithm greatly reduces the computational amount while keeping the performance approximately. |
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| Keywords: | de-interlace adaptive motion estimation Kalman filter motion compensation |
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