In this paper, we propose a luminance and color correction scheme for multiview image compression for a 3-DTV system. According to characteristics of luminance and chrominance, we propose a 3-D discrete cosine transfo...
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In this paper, we propose a luminance and color correction scheme for multiview image compression for a 3-DTV system. According to characteristics of luminance and chrominance, we propose a 3-D discrete cosine transform (3-D DCT) for 3-D imagecompression. Then, a cubic memory-based 3-D DCT is proposed for 3-D imagecompression in this paper. 3-D display technology has become an important technology lately. TFT-based multiview 3-D display has the advantage of convenient setup, mass production, and a large amount of 3-D content support, making it a popular 3-D display product. However, multiview 3-D signals need huge storage space and wide channel bandwidth, especially when view number is larger than two views. To overcome the obstacles, we propose a 3-D DCT component based on cubic memory to perform 3-D imagecompression in this paper. The presented architecture reduces a great quantity of memory space and provides efficient 3-D signal storage.
In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely na...
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In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely navigate in a three-dimensional scene. The interactivity brings new challenges in addition to the classical rate-distortion tradeoff, which considers only the compression performance and viewing quality. On one hand, interactivity necessitates sufficient viewpoints for richer navigation;on the other hand, it requires to provide low bandwidth and delay costs for smooth navigation during view transitions. In this paper, we formally describe the novel tradeoffs posed by the navigation interactivity and classical rate-distortion criterion. Based on an original formulation, we look for the optimal design of the data representation by introducing novel rate and distortion models and practical solving algorithms. Experiments show that the proposed data representation method outperforms the baseline solution by providing lower resource consumptions and higher visual quality in all navigation configurations, which certainly confirms the potential of the proposed data representation in practical interactive navigation systems.
In this paper, we propose two multiview image compression methods. The basic concept of both schemes is the layer-based representation, in which the captured three-dimensional (3D) scene is partitioned into layers eac...
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ISBN:
(纸本)9780819487452
In this paper, we propose two multiview image compression methods. The basic concept of both schemes is the layer-based representation, in which the captured three-dimensional (3D) scene is partitioned into layers each related to a constant depth in the scene. The first algorithm is a centralized scheme where each layer is de-correlated using a separable multi-dimensional wavelet transform applied across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. Although the method achieves a high compression rate, the joint encoding approach requires the transmission of all data to the users. By contrast, in an interactive setting, the users request only a subset of the captured images, but in an unknown order a priori. We address this scenario in the second algorithm using Distributed Source Coding (DSC) principles which reduces the inter-view redundancy and facilitates random access at the image level. We demonstrate that the proposed centralized and interactive methods outperform H.264/MVC and JPEG 2000, respectively.
Effectively coding multiview visual content is an indispensable research topic because multiviewimage and video that provide greatly enhanced viewing experiences often contain huge amounts of data. Generally, convent...
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Effectively coding multiview visual content is an indispensable research topic because multiviewimage and video that provide greatly enhanced viewing experiences often contain huge amounts of data. Generally, conventional hybrid predictive-coding methodologies are adopted to address the compression by exploiting the temporal and interviewpoint redundancy existing in a multiviewimage or video sequences. However, their key yet time-consuming component, motion estimation (ME), is usually not efficient in interviewpoint prediction or disparity estimation (DE), because interviewpoint disparity is completely different from temporal motion existing in the conventional video. Targeting a generic fast DE framework for interviewpoint prediction, we propose a novel DE technique in this paper to accelerate the disparity search by employing epipolar geometry. Theoretical analysis, optimal disparity vector distribution histograms, and experimental results show that the proposed epipolar geometry-based DE can greatly reduce search region and effectively track large and irregular disparity, which is typical in convergent multiview camera setups. Compared with the existing state-of-the-art fast ME approaches, our proposed DE can obtain a similar coding efficiency while achieving a significant speedup for interviewpoint prediction and coding. Moreover, a robustness study shows that the proposed DE algorithm is insensitive to the epipolar geometry estimation noise. Hence, its wide application for multiviewimage and video coding is promising.
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