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Functional coding of video using a shape-adaptive DCT algorithm andan object-based motion prediction toolbox

机译:使用形状自适应DCT算法和基于对象的运动预测工具箱对视频进行功能编码

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This paper presents an object-based layered video coding scheme which achieves very high compression efficiency along with the provision for advanced content-based functionalities, e.g., content-based scalability or content-based access and manipulation of video data. In a first step, a video sequence is segmented into several arbitrarily shaped “object layers.” To achieve the desired content-based functionalities, a baseline shape-adaptive discrete cosine transform (DCT) coding algorithm is introduced which can be seen as an extension of conventional block-based DCT coding schemes (e.g., H.261, H.263, MPEG-1, or MPEG-2) toward coding of arbitrarily shaped image content. In order to increase compression efficiency, the baseline object-based layered approach can be extended with an object-based motion prediction toolbox. Using this toolbox, the coding scheme can potentially select specific prediction techniques for every object layer to be coded. To illustrate the concept, an extension of the baseline shape-adaptive DCT algorithm with a technique for global background motion estimation and compensation is described which significantly improves the compression efficiency of suitable video sequences compared to standard MPEG coding schemes
机译:本文提出了一种基于对象的分层视频编码方案,该方案可实现非常高的压缩效率,并提供了基于内容的高级功能,例如基于内容的可伸缩性或基于内容的视频数据访问和操作。第一步,将视频序列分割为几个任意形状的“对象层”。为了实现所需的基于内容的功能,引入了基线形状自适应离散余弦变换(DCT)编码算法,该算法可以看作是常规基于块的DCT编码方案的扩展(例如,H.261,H.263, MPEG-1或MPEG-2),以对任意形状的图像内容进行编码。为了提高压缩效率,可以使用基于对象的运动预测工具箱扩展基于对象的基线分层方法。使用此工具箱,编码方案可以潜在地为要编码的每个对象层选择特定的预测技术。为了说明这一概念,描述了使用全局背景运动估计和补偿技术对基线形状自适应DCT算法的扩展,与标准MPEG编码方案相比,该技术显着提高了合适视频序列的压缩效率。

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