The multi-view video coding improves the coding efficiency by utilizing motion-compensated prediction (MCP) and disparity-compensated prediction (DCP). However, the complexity of the inter frame prediction is very hig...
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The multi-view video coding improves the coding efficiency by utilizing motion-compensated prediction (MCP) and disparity-compensated prediction (DCP). However, the complexity of the inter frame prediction is very high, especially when the rate-distortion optimization is used. This paper presents a fast inter frame prediction algorithm to reduce the complexity. Firstly the prediction type is decided according to reference frames. Then some unuseful search regions in view direction are removed. Finally a fast inter mode decision strategy is proposed based on the relationship between MCP and DCP. Experimental results verify that the proposed algorithm can greatly increase the speed of prediction with negligible loss of coding efficiency.
In this paper we present a bit allocation approach based on motion vector analysis for improved rate-distortion performance. Bit allocation is done at the macroblock level such that the macroblock with high priority i...
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In this paper we present a bit allocation approach based on motion vector analysis for improved rate-distortion performance. Bit allocation is done at the macroblock level such that the macroblock with high priority is coded finely and the one with low priority is coded coarsely. In order to calculate macroblock priorities, first reference counts for each pixel are determined through motion vector analysis. A reference count of a pixel is defined as total number of pixels in the remaining GOP which use that pixel as a reference. Then macroblock wise reference counts is obtained by summing the pixel wise reference counts, which are then scaled and prioritized. Based upon the priority value the given fixed quant of each frame is modulated at the macroblock level. The algorithm is applied to H.264/AVC encoding and PSNR gains of up to 1.4 dB are achieved
We revisit the classic problem of developing a spatial correlation model for natural images and videos by proposing a conditional correlation model for relatively nearby pixels that is dependent upon five parameters. ...
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ISBN:
(纸本)9781424413973
We revisit the classic problem of developing a spatial correlation model for natural images and videos by proposing a conditional correlation model for relatively nearby pixels that is dependent upon five parameters. The conditioning is on local texture and the optimal parameters can be calculated for a specific image or video with a mean absolute error (MAE) usually smaller than 5%. We use this conditional correlation model to calculate the conditional rate distortion function when universal side information is available at both the encoder and the decoder. We demonstrate that this side information, when available, can save as much as 1 bit per pixel for selected videos at low distortions. We further study the scenario when the video frame is processed in macroblocks (MBs) or smaller blocks and calculate the rate distortion bound when the texture information is coded losslessly and optimal predictive coding is utilized to partially incorporate the correlation between the neighboring MBs or blocks.
Wyner-Ziv coding has been recognized as the most popular method up to now. For traditional WZC, side information is generated from intra-coded frames for use in the decoding of WZ frames. The unit for intra-coding is ...
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Wyner-Ziv coding has been recognized as the most popular method up to now. For traditional WZC, side information is generated from intra-coded frames for use in the decoding of WZ frames. The unit for intra-coding is a frame and the distance between key-frames is kept constant. In this paper, the unit for intra-coding is a block, and the temporal distance between two consecutive key blocks can varying with time. A block is assigned a mode (WZ or intra-coded), depending on the result of spatio-temporal analysis, and encoded in an alternative manner. This strategy improves the overall coding efficiency, while maintaining a low encoder complexity. The performance gain can achieve up to 6 dB with respect to the traditional pixel-domain WZC.
This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achi...
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This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achieves 7-35 times faster compression than existing methods such as JPEG2000 and JPEG-LS, at similar compression ratios. Additionally, unlike JPEG-LS, it supports additional features such as progressive decompression using resolution scaling. An implementation of this codec will be used in the Japan Aerospace Exploration Agency (JAXA)'s Venus Climate Orbiter mission (PLANET-C).
Average consensus algorithms are gossiping protocols for averaging original measurements taken at different sensors. Without any communication rate restrictions, the algorithms ideally allow every node state to conver...
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Average consensus algorithms are gossiping protocols for averaging original measurements taken at different sensors. Without any communication rate restrictions, the algorithms ideally allow every node state to converge to the initial average after some iterations. Noting that brute force quantization is highly suboptimal given the rich temporal and spatial correlation of the messages exchanged, in our previous work we proposed two source coding methods, predictive coding and Wyner-Ziv coding which achieve convergence with vanishing quantization rates in the case of block coding. Both methods ideally require complete information about the network parameters and topology as well as processing and storage of the past state values. The knowledge of the network parameters is not a practical requirement, especially considering that one is implementing average consensus algorithms that are decentralized. In this study we show that as the node density increases or in homogeneously distributed networks, the encoder and decoder parameters become independent on the network size and specific location. We also lower bound the error performance of the predictive coding scheme in terms of eigenvalues of the connectivity and initial state covariance matrices. We show the relation between MSE behavior of the algorithm and network connectivity, as well as quantization rate.
The hexagon-based search pattern (HEXBS) algorithm yields fewer search points required for motion estimation, compared to square-shaped and diamond-shape patterns. In this paper, we propose a fast motion estimation al...
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The hexagon-based search pattern (HEXBS) algorithm yields fewer search points required for motion estimation, compared to square-shaped and diamond-shape patterns. In this paper, we propose a fast motion estimation algorithm to further reduce the search points demanded by HEXBS algorithm. After exploiting the statistical property of motion vectors of the neighboring blocks, the number of selected candidate points on the hexagon endpoints will be lower than the original HEXBS algorithm. Thus, the motion estimation efficiency can be improved in such a way. Experimental results show that the proposed algorithm decreases 57.62% average search points, compared to HEXBS algorithm, with only slight quality degradation.
We present a low-delay, constrained-entropy, backward adaptive, linear-predictive audio coder with low computational complexity. In contrast to most practical linear-predictive coders, the coder facilitates the exploi...
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We present a low-delay, constrained-entropy, backward adaptive, linear-predictive audio coder with low computational complexity. In contrast to most practical linear-predictive coders, the coder facilitates the exploitation of reverse waterfilling. The coder uses time-invariant quantization step size and constrained-entropy coding, thus eliminating the convergence problems of backward adaptation near signal transitions. Yet rate variations are kept small by the usage of a mixture model density for the signal. The mixture model has the backward adapted model and a second model as components and the component probability is transmitted. Experimental results confirm the advantages of the coder structure and show that the coder provides good overall performance.
For various 3D Animation processing, representing mesh geometry in local rather the world coordinate systems is very useful. One can investigate the representation of vertex locations relative to a local coordinate fr...
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For various 3D Animation processing, representing mesh geometry in local rather the world coordinate systems is very useful. One can investigate the representation of vertex locations relative to a local coordinate frame (LCF) in the compression of dynamic 3D meshes. Unlike the world coordinates, which scatter in a wide range and show non linear behavior of the vertices, the local coordinates exhibit a large clustering behavior of the vertex over time. This property is very useful for exploiting a large coherence over the vertex trajectory and between neighboring vertices. In this paper, we discuss the use of the LCF in mesh encoding and we introduce a new and simple predictive scheme for single-rate compression for animated meshes. Our geometry encoding strategy is based on a region growing encoding order and only the delta vectors between original and predicted locations are encoded in a local coordinate system, which splits into two tangential and one normal components. Our approach is simple, efficient and well suited for real time applications.
This paper proposes a novel 3D piecewise planar reconstruction algorithm, which utilizes the statistical error between a particular frame and its prediction to refine a coarse 3D piecewise planar representation. The a...
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This paper proposes a novel 3D piecewise planar reconstruction algorithm, which utilizes the statistical error between a particular frame and its prediction to refine a coarse 3D piecewise planar representation. The algorithm aims utilization of 3D scene geometry to remove the visual redundancy between frame pairs in any predictive coding scheme. This approach associates the rate increase with the quality of representation for determining an efficient description for a given budget. The preliminary experiments on synthetic and real data indicate the validity of the rate-distortion based approach.
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