Scalable fusion using a 3D dual tree wavelet transform
Scalable fusion using a 3D dual tree wavelet transform
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使用 3D 双树小波变换的可扩展融合
DOI：
10.1049/ic.2011.0172
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Hill P
中科院分区：
文献类型：
--
作者：
Hill P
本文介绍了一种能够在压缩域中融合两组或多组多模态视频的新颖系统。这是在没有漂移的情况下实现的，并产生提供细粒度可扩展性的嵌入式比特流。由于标准视频编码技术中预测循环的复杂性，之前在压缩视频域中进行融合的尝试一直是不可能的。该压缩系统基于优化的时空编解码器，使用 3D 离散双树小波变换（DDWT）以及位平面编码方法 SPIHT 和系数稀疏过程（噪声整形）。由于变换的方向（空间和时间）选择性，这些方法一起能够有效地编码视频序列，而无需运动补偿。这使得可扩展的压缩域融合没有漂移。这导致在客户端接收能力可变的动态带宽环境中实现极其灵活的融合场景。
This paper introduces a novel system that is able to fuse two or more sets of multimodal videos in the compressed domain. This is achieved without drift and produces an embedded bitstream that offers fine grain scalability. Previous attempts to fuse in the compressed video domain have been not been possible due to the complications of predictive loops within standard video encoding techniques. The compression system is based on an optimised spatio-temporal codec using the 3D Discrete Dual-tree Wavelet Trans- form (DDWT) together with bit plane encoding method SPIHT and a coefficient sparsification process (noise shaping). Together, these methods are able to efficiently encode a video sequence without the need for motion compensation due to the directional (in space and time) selectivity of the transform. This enables scalable compressed domain fusion without drift. This results in extremely flexible fusion scenarios in dynamic bandwidth environments where there are variable client receiving capabilities.