35 research outputs found

    HEVC-based 3D holoscopic video coding using self-similarity compensated prediction

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    Holoscopic imaging, also known as integral, light field, and plenoptic imaging, is an appealing technology for glassless 3D video systems, which has recently emerged as a prospective candidate for future image and video applications, such as 3D television. However, to successfully introduce 3D holoscopic video applications into the market, adequate coding tools that can efficiently handle 3D holoscopic video are necessary. In this context, this paper discusses the requirements and challenges for 3D holoscopic video coding, and presents an efficient 3D holoscopic coding scheme based on High Efficiency Video Coding (HEVC). The proposed 3D holoscopic codec makes use of the self-similarity (SS) compensated prediction concept to efficiently explore the inherent correlation of the 3D holoscopic content in Intra- and Inter-coded frames, as well as a novel vector prediction scheme to take advantage of the peculiar characteristics of the SS prediction data. Extensive experiments were conducted, and have shown that the proposed solution is able to outperform HEVC as well as other coding solutions proposed in the literature. Moreover, a consistently better performance is also observed for a set of different quality metrics proposed in the literature for 3D holoscopic content, as well as for the visual quality of views synthesized from decompressed 3D holoscopic content.info:eu-repo/semantics/submittedVersio

    Weighted bi-prediction for light field image coding

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    Light field imaging based on a single-tier camera equipped with a microlens array – also known as integral, holoscopic, and plenoptic imaging – has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require developing adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, self-similarity compensated prediction is a non-local spatial prediction scheme based on block matching that has been shown to achieve high efficiency for light field image coding based on the High Efficiency Video Coding (HEVC) standard. As previously shown by the authors, this is possible by simply averaging two predictor blocks that are jointly estimated from a causal search window in the current frame itself, referred to as self-similarity bi-prediction. However, theoretical analyses for motion compensated bi-prediction have suggested that it is still possible to achieve further rate-distortion performance improvements by adaptively estimating the weighting coefficients of the two predictor blocks. Therefore, this paper presents a comprehensive study of the rate-distortion performance for HEVC-based light field image coding when using different sets of weighting coefficients for self-similarity bi-prediction. Experimental results demonstrate that it is possible to extend the previous theoretical conclusions to light field image coding and show that the proposed adaptive weighting coefficient selection leads to up to 5 % of bit savings compared to the previous self-similarity bi-prediction scheme.info:eu-repo/semantics/acceptedVersio

    Light field image coding with jointly estimated self-similarity bi-prediction

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    This paper proposes an efficient light field image coding (LFC) solution based on High Efficiency Video Coding (HEVC) and a novel Bi-prediction Self-Similarity (Bi-SS) estimation and compensation approach to efficiently explore the inherent non-local spatial correlation of this type of content, where two predictor blocks are jointly estimated from the same search window by using a locally optimal rate constrained algorithm. Moreover, a theoretical analysis of the proposed Bi-SS prediction is also presented, which shows that other non-local spatial prediction schemes proposed in literature are suboptimal in terms of Rate-Distortion (RD) performance and, for this reason, can be considered as restricted cases of the jointly estimated Bi-SS solution proposed here. These theoretical insights are shown to be consistent with the presented experimental results, and demonstrate that the proposed LFC scheme is able to outperform the benchmark solutions with significant gains with respect to HEVC (with up to 61.1% of bit savings) and other state-of-the-art LFC solutions in the literature (with up 16.9% of bit savings).info:eu-repo/semantics/acceptedVersio

    HEVC-based light field image coding with bi-predicted self-similarity compensation

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    This paper proposes an efficient light field image coding (LFC) solution based on High Efficiency Video Coding (HEVC). The proposed light field codec makes use of the self-similarity (SS) compensated prediction concept to efficiently explore the inherent correlation of this type of content. To further improve the coding performance, a bi-predicted SS estimation and SS compensation is proposed, where the candidate predictor can be also devised as a linear combination of two blocks within the same search window. In addition, an improved vector prediction scheme is also used to take advantage of the particular characteristics of the SS prediction vectors. Experimental results show that the proposed LFC scheme is able to outperform the benchmark solutions with significant gains.info:eu-repo/semantics/acceptedVersio

    Light field HEVC-based image coding using locally linear embedding and self-similarity compensated prediction

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    Light field imaging is a promising new technology that allows the user not only to change the focus and perspective after taking a picture, as well as to generate 3D content, among other applications. However, light field images are characterized by large amounts of data and there is a lack of coding tools to efficiently encode this type of content. Therefore, this paper proposes the addition of two new prediction tools to the HEVC framework, to improve its coding efficiency. The first tool is based on the local linear embedding-based prediction and the second one is based on the self-similarity compensated prediction. Experimental results show improvements over JPEG and HEVC in terms of average bitrate savings of 71.44% and 31.87%, and average PSNR gains of 4.73dB and 0.89dB, respectively.info:eu-repo/semantics/acceptedVersio

    Locally linear embedding-based prediction for 3D holoscopic image coding using HEVC

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    Holoscopic imaging is a prospective acquisition and display solution for providing true 3D content and fatigue-free 3D visualization. However, efficient coding schemes for this particular type of content are needed to enable proper storage and delivery of the large amount of data involved in these systems. Therefore, this paper proposes an alternative HEVC-based coding scheme for efficient representation of holoscopic images. In this scheme, some directional intra prediction modes of the HEVC are replaced by a more efficient prediction framework based on locally linear embedding techniques. Experimental results show the advantage of the proposed prediction for 3D holoscopic image coding, compared to the reference HEVC standard as well as previously presented approaches in this field.info:eu-repo/semantics/submittedVersio

    Improved inter-layer prediction for Light field content coding with display scalability

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    Light field imaging based on microlens arrays - also known as plenoptic, holoscopic and integral imaging - has recently risen up as feasible and prospective technology due to its ability to support functionalities not straightforwardly available in conventional imaging systems, such as: post-production refocusing and depth of field changing. However, to gradually reach the consumer market and to provide interoperability with current 2D and 3D representations, a display scalable coding solution is essential. In this context, this paper proposes an improved display scalable light field codec comprising a three-layer hierarchical coding architecture (previously proposed by the authors) that provides interoperability with 2D (Base Layer) and 3D stereo and multiview (First Layer) representations, while the Second Layer supports the complete light field content. For further improving the compression performance, novel exemplar-based inter-layer coding tools are proposed here for the Second Layer, namely: (i) an inter-layer reference picture construction relying on an exemplar-based optimization algorithm for texture synthesis, and (ii) a direct prediction mode based on exemplar texture samples from lower layers. Experimental results show that the proposed solution performs better than the tested benchmark solutions, including the authors' previous scalable codec.info:eu-repo/semantics/acceptedVersio

    Light field coding with field of view scalability and exemplar-based inter-layer prediction

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    Light field imaging based on microlens arrays—a.k.a. holoscopic, plenoptic, and integral imaging—has currently risen up as a feasible and prospective technology for future image and video applications. However, deploying actual light field applications will require identifying more powerful representations and coding solutions that support arising new manipulation and interaction functionalities. In this context, this paper proposes a novel scalable coding solution that supports a new type of scalability, referred to as field-of-view scalability. The proposed scalable coding solution comprises a base layer compliant with the High Efficiency Video Coding (HEVC) standard, complemented by one or more enhancement layers that progressively allow richer versions of the same light field content in terms of content manipulation and interaction possibilities. In addition, to achieve high-compression performance in the enhancement layers, novel exemplar-based interlayer coding tools are also proposed, namely: 1) a direct prediction based on exemplar texture samples from lower layers and 2) an interlayer compensated prediction using a reference picture that is built relying on an exemplar-based algorithm for texture synthesis. Experimental results demonstrate the advantages of the proposed scalable coding solution to cater to users with different preferences/requirements in terms of interaction functionalities, while providing better rate- distortion performance (independently of the optical setup used for acquisition) compared to HEVC and other scalable light field coding solutions in the literature.info:eu-repo/semantics/acceptedVersio

    Light field image compression

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    Light field imaging based on a single-tier camera equipped with a micro-lens array has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require identifying adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, this chapter presents some of the most recent light field image coding solutions that have been investigated. After a brief review of the current state of the art in image coding formats for light field photography, an experimental study of the rate-distortion performance for different coding formats and architectures is presented. Then, aiming at enabling faster deployment of light field applications and services in the consumer market, a scalable light field coding solution that provides backward compatibility with legacy display devices (e.g., 2D, 3D stereo, and 3D multiview) is also presented. Furthermore, a light field coding scheme based on a sparse set of microimages and the associated blockwise disparity is also presented. This coding scheme is scalable with three layers such that the rendering can be performed with the sparse micro-image set, the reconstructed light field image, and the decoded light field image.info:eu-repo/semantics/acceptedVersio
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