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Video Compression Based on Wavelet Transform and DBMA with Motion Compensation

机译:基于小波变换和带运动补偿的DBMA的视频压缩

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In video compression, it can reduce the redundant information efficiently by motion estimation (ME) and motion compensation (MC), and less code is used to encode as much information as possible. In this paper, I frame encoding adopts wavelet transform and set partitioning in hierarchical trees (SPIHT) algorithm; for P frames, each frame sets the reconstructed frame of its previous frame as a reference frame, and then P frames proceed to code with ME and MC. In the step of ME, trading off between accuracy and computational complexity, adaptive fast search (AFS) algorithm combining with nodal search-based deformable block matching algorithm (NS-DBMA) is adopted to search for the matched block; and then in the MC process, wavelet transform combining with zerotree entropy (ZTE) algorithm is adopted according to the characteristics of residual image data. Meanwhile rate control is carried out in ZTE algorithm. Experimental results show that the proposed algorithm performs well for video sequences with complex motion and rich details, and reduces blocking artifacts obviously.
机译:在视频压缩中,它可以通过运动估计(ME)和运动补偿(MC)有效地减少冗余信息,并且使用较少的代码来编码尽可能多的信息。本文的I帧编码采用小波变换和层次树中的集划分(SPIHT)算法。对于P帧,每个帧将其前一帧的重构帧设置为参考帧,然后P帧继续使用ME和MC进行编码。在ME的步骤中,在精度和计算复杂度之间进行权衡,采用自适应快速搜索(AFS)算法和基于节点搜索的可变形块匹配算法(NS-DBMA)进行搜索;然后在MC处理中,根据残差图像数据的特点,采用小波变换结合零树熵(ZTE)算法。同时采用中兴通讯算法进行速率控制。实验结果表明,该算法对运动复杂,细节丰富的视频序列具有良好的效果,并且明显减少了块状伪像。

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