Scalable video compression via overcomplete motion compensated wavelet coding

Li, Xin

doi:10.1016/j.image.2004.05.006

Cited by 28 publications

(16 citation statements)

References 39 publications

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“…Since decimation also causes frequency aliasing, phase-based edge detection methods are not effective. Inspired by the motion compensation technique performed in the overcomplete wavelet space [20], orientation distribution is estimated in the overcomplete wavelet space to avoid problems brought by decimation.…”

Section: A Orientation Distribution Estimation In the Overcomplete Wmentioning

confidence: 99%

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Scalable Video Compression Framework With Adaptive Orientational Multiresolution Transform and Nonuniform Directional Filterbank Design

Xiong

Zhu

Ma³

et al. 2011

IEEE Trans. Circuits Syst. Video Technol.

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Abstract-Although wavelet-based scalable video coding becomes the state-of-the-art video compression engine for its adaptability to heterogeneous networks and clients, a large number of attempts have been made to integrate local directionality onto discrete wavelet transform to explore the intrinsic geometrical structures. Taking into consideration that the contours and textures scattered in different scales change their directional resolutions as their curvatures change, we investigate adaptive directional resolutions along scales to achieve the dual (scale and orientation) multiresolution transform. This paper proposes nonuniform directional frequency decompositions for video representation and approximation, and exploits the nonuniformity of orientation multiresolution distribution and designs nonuniform directional filter banks to make the geometrical transform more sparse and efficient. The nonuniform directional frequency decomposition under arbitrary scales is fulfilled by a nonsymmetric binary tree (NSBT) topology structure with nonuniform directional filterbank design. In turn, the proposed scalable video coding framework, called DMSVC, is enriched with the dual multiresolution transform. Each temporal subband through motion compensated temporal filtering is further decomposed into multiscale subbands, and the highpass wavelet subspaces are divided into an arbitrary number of directional subspaces in alignment with the orientation distribution via phase congruency to establish NSBT. The paraunitary perfect reconstruction condition is provided through a polyphase identical form of filter bank. Comparing with the isolated wavelet basis, our transform provides a greater correlated set of localized and anisotropic basis functions. The spatio-temporal subband coefficients are coded by a 3-D ESCOT entropy coding algorithm which is adopted to match the structure of NSBT. Experimental results show that the reconstructed video frames DMSVC in the proposed DMSVC scheme have better visual quality than existing scalable video coding schemes. It could produce higher compression ratio on video sequences full of directional edges and textures.

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Section: A Orientation Distribution Estimation In the Overcomplete Wmentioning

confidence: 99%

“…Proposition 1: Suppose we divide W s k into L subspaces with Q different orientation multiresolutions ({r 1 , r 2 , · · · , r Q }), and partition operator is applied to W s k for r min = min{r 1 , r 2 , · · · , r Q } times iteratively according to (20), that is…”

Section: B Multiresolution Analysismentioning

confidence: 99%

Scalable Video Compression Framework With Adaptive Orientational Multiresolution Transform and Nonuniform Directional Filterbank Design

Xiong

Zhu

Ma³

et al. 2011

IEEE Trans. Circuits Syst. Video Technol.

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“…The spatial scalability in these schemes is commonly provided by spatial wavelet transform. Based on the relationship between spatial transform and temporal transform, the structures of existing wavelet video coding schemes can be roughly divided into three categories: T+2D [7]- [19], 2D+T [22]- [26], multiresolution T+2D [27]- [33].…”

Section: Introductionmentioning

confidence: 99%

In-Scale Motion Compensation for Spatially Scalable Video Coding

Xiong¹,

2008

IEEE Trans. Circuits Syst. Video Technol.

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In existing pyramid-based spatially scalable coding schemes, such as H.264/MPEG-4 SVC (scalable video coding), video frame at a certain high-resolution layer is mainly predicted either from the same frame at the next lower resolution layer, or from the temporal neighboring frames within the same resolution layer. But these schemes fail to exploit both kinds of correlation simultaneously and therefore cannot remove the redundancies among resolution layers efficiently. This paper extends the idea of spatiotemporal subband transform and proposes a general in-scale motion compensation technique for pyramid-based spatially scalable video coding. Video frame at each high-resolution layer is partitioned into two parts in frequency. Prediction for the lowpass part is derived from the next lower resolution layer, whereas prediction for the highpass part is obtained from neighboring frames within the same resolution layer, to further utilize temporal correlation. In this way, both kinds of correlation are exploited simultaneously and the cross-resolution-layer redundancy can be highly removed. Furthermore, this paper also proposes a macroblock-based adaptive in-scale technique for hybrid spatial and SNR scalability. Experimental results show that the proposed techniques can significantly improve the spatial scalability performance of H.264/MPEG-4 SVC, especially when the bit-rate ratio of lower resolution bit stream to higher resolution bit stream is considerable.Index Terms-H.264/MPEG-4 SVC, in-scale motion compensation, inter-layer prediction, scalable video coding, spatial scalability.

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“…We make use of the anisotropic property of the motion field in shiftinvariant wavelet domain to develop an anisotropic double cross search (ADCS) algorithm using multiresolution-spatio-temporal context for fast motion estimation in shift-invariant wavelet domain. Due to the multiresolution nature, both the proposed approaches can be applied to scalable wavelet video coding systems based on overcomplete in-band motion compensated temporal filtering [1,9,18]. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%