MOTION DETECTION IN COMPRESSED VIDEO USING MACROBLOCK CLASSIFICATION

M. Usha
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引用次数: 4

Abstract

In this paper, to detect the moving objects between frames in compressed video and to obtain the best compression video and the noiseless video. We describe a video in which frames by classifying macroblocks (MB), and describe motion estimation (ME), motion vector field (MV) and motion compensation (MC). we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content based on the motion vector. MB class information video applications such as shot change detection, motion discontinuity detection, Outlier rejection for global motion estimation. To reduce the noise and to improve the clarity of the compressed video by using contrast limited adaptive histogram equalization (CLAHE) Algorithm.
使用宏块分类的压缩视频中的运动检测
本文主要研究压缩视频帧间运动目标的检测,以获得最佳的压缩视频和无噪视频。本文通过对宏块(MB)进行分类来描述视频帧,并对运动估计(ME)、运动矢量场(MV)和运动补偿(MC)进行了描述。我们提出将每个视频帧的macroblock划分为不同的类,并利用这类信息来描述基于运动向量的帧内容。MB类信息视频应用,如镜头变化检测,运动不连续检测,全局运动估计的Outlier抑制。采用限制对比度的自适应直方图均衡化(CLAHE)算法来降低噪声,提高压缩视频的清晰度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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