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light field image coding Based on Hybrid Data Representation

IEEE ACCESS 2020年 8卷 115728-115744页

作者： Monteiro, Ricardo J. S. Rodrigues, Nuno M. M. Faria, Sergio M. M. Nunes, Paulo J. L. Inst Telecomunicacoes P-1049001 Lisbon Portugal Inst Univ Lisboa ISCTE IUL P-1649026 Lisbon Portugal Inst Telecomunicacoes P-2411901 Leiria Portugal Inst Politecn Leiria Escola Super Tecnol & Gestao P-2411901 Lisbon Portugal

This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-of-the-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVC-based pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and -14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVC-based benchmark, as well as MuLE and WaSP.

关键词： light field representation light field image coding HEVC pseudo-video sequence spatial pixel prediction least squares prediction

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Lenslet light field image coding: Classifying, Reviewing and Evaluating

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2021年第1期31卷 339-354页

作者： Brites, Catarina Ascenso, Joao Pereira, Fernando Univ Lisbon Inst Super Tecn Inst Telecomunicacoes P-1049001 Lisbon Portugal

In recent years, visual sensors have been quickly improving, notably targeting richer acquisitions of the light present in a visual scene. In this context, the so-called lenslet light field (LLF) cameras are able to go beyond the conventional 2D visual acquisition models, by enriching the visual representation with directional light measures for each pixel position. LLF imaging is associated to large amounts of data, thus critically demanding efficient coding solutions in order applications involving transmission and storage may be deployed. For this reason, considerable research efforts have been invested in recent years in developing increasingly efficient LLF imaging coding (LLFIC) solutions. In this context, the main objective of this paper is to review and evaluate some of the most relevant LLFIC solutions in the literature, guided by a novel classification taxonomy, which allows better organizing this field. In this way, more solid conclusions can be drawn about the current LLFIC status quo, thus allowing to better drive future research and standardization developments in this technical area.

关键词： Cameras Taxonomy Encoding Two dimensional displays Visualization Spatial resolution light field image coding lenslet taxonomy perspective image micro-image

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light field image coding with flexible viewpoint scalability and random access

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SIGNAL PROCESSING-image COMMUNICATION 2021年 94卷 116202-116202页

作者： Monteiro, Ricardo J. S. Rodrigues, Nuno M. M. Faria, Sergio M. M. Nunes, Paulo J. L. Inst Telecomunicacoes P-1049001 Lisbon Portugal Inst Univ Lisboa ISCTE IUL P-1649026 Lisbon Portugal Inst Telecomunicacoes P-2411901 Leiria Portugal Polytech Leiria Escola Super Tecnol & Gestao ESTG P-2411901 Leiria Portugal

This paper proposes a novel light field image compression approach with viewpoint scalability and random access functionalities. Although current state-of-the-art image coding algorithms for light fields already achieve high compression ratios, there is a lack of support for such functionalities, which are important for ensuring compatibility with different displays/capturing devices, enhanced user interaction and low decoding delay. The proposed solution enables various encoding profiles with different flexible viewpoint scalability and random access capabilities, depending on the application scenario. When compared to other state-of-the-art methods, the proposed approach consistently presents higher bitrate savings (44% on average), namely when compared to pseudo-video sequence coding approach based on HEVC. Moreover, the proposed scalable codec also outperforms MuLE and WaSP verification models, achieving average bitrate saving gains of 37% and 47%, respectively. The various flexible encoding profiles proposed add fine control to the image prediction dependencies, which allow to exploit the tradeoff between coding efficiency and the viewpoint random access, consequently, decreasing the maximum random access penalties that range from 0.60 to 0.15, for lenslet and HDCA light fields.

关键词： light field image coding Viewpoint scalability Viewpoint random access HEVC

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Optimized Reference Picture Selection for light field image coding 27

Optimized Reference Picture Selection for Light Field Image ...

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27th European Signal Processing Conference (EUSIPCO)

作者： Monteiro, Ricardo J. S. Rodrigues, Nuno M. M. Faria, Sergio M. M. Nunes, Paulo J. L. Inst Telecomunicacoes Lisbon Portugal Inst Univ Lisboa ISCTE IUL Lisbon Portugal Inst Politecn Leiria ESTG Leiria Portugal

ISBN: (数字)9789082797039

ISBN: (纸本)9789082797039

This paper proposes a new reference picture selection method for light field image coding using the pseudo-video sequence (PVS) format. State-of-the-art solutions to encode light field images using the PVS format rely on video coding standards to exploit the inter-view redundancy between each sub-aperture image (SAI) that composes the light field. However, the PVS scanning order is not usually considered by the video codec. The proposed solution signals the PVS scanning order to the decoder, enabling implicit optimized reference picture selection for each specific scanning order. With the proposed method each reference picture is selected by minimizing the Euclidean distance to the current SAL being encoded. Experimental results show that, for the same PVS scanning order, the proposed optimized reference picture selection codec outperforms HEVC video coding standard for light field image coding, up to 50% in terms of bitrate savings.

关键词： light field image coding Pseudo-video sequence optimized reference picture selection HEVC

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light field image coding using High Order Prediction Training 26

Light Field Image Coding using High Order Prediction Trainin...

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European Signal Processing Conference (EUSIPCO)

作者： Monteiro, Ricardo J. S. Nunes, Paulo J. L. Faria, Sergio M. M. Rodrigues, Nuno M. M. Inst Telecomunicacoes Lisbon Portugal ISCTE IUL Lisbon Portugal Inst Telecomunicacoes Leiria Portugal Inst Politecn Leiria ESTG Leiria Portugal

ISBN: (纸本)9789082797015

This paper proposes a new method for light field image coding relying on a high order prediction mode based on a training algorithm. The proposed approach is applied as an Intra prediction method based on a two-stage block-wise high order prediction model that supports geometric transformations up to eight degrees of freedom. light field images comprise an array of micro-images that are related by complex perspective deformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low order translational prediction models. The proposed prediction mode is able to exploit the non-local spatial redundancy introduced by light field image structure and a training algorithm is applied on different micro-images that are available in the reference region aiming at reducing the amount of signaling data sent to the receiver. The training direction that generates the most efficient geometric transformation for the current block is determined in the encoder side and signaled to the decoder using an index. The decoder is therefore able to repeat the high order prediction training to generate the desired geometric transformation. Experimental results show bitrate savings up to 12.57% and 50.03% relatively to a light field image coding solution based on low order prediction without training and HEVC, respectively.

关键词： light field image coding HEVC High Order Prediction Training Geometric Transformations

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light field image coding: objective performance assessment of Lenslet and 4D LF data representations 41

Light field image coding: objective performance assessment o...

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Conference on Applications of Digital image Processing XLI

ISBN: (数字)9781510620766

ISBN: (纸本)9781510620766

State-of-the-art light field (LF) image coding solutions, usually, rely in one of two LF data representation formats: Lenslet or 4D LF. While the Lenslet data representation is a more compact version of the LF, it requires additional camera metadata and processing steps prior to image rendering. On the contrary, 4D LF data, consisting of a stack of sub-aperture images, provides a more redundant representation requiring, however, minimal side information, thus facilitating image rendering. Recently, JPEG Pleno guidelines on objective evaluation of LF image coding defined a processing chain that allows to compare different 4D LF data codecs, aiming to facilitate codec assessment and benchmark. Thus, any codec that does not rely on the 4D LF representation needs to undergo additional processing steps to generate an output comparable to a reference 4D LF image. These additional processing steps may have impact on the quality of the reconstructed LF image, especially if color subsampling format and bit depth conversions have been performed. Consequently, the influence of these conversions needs to be carefully assessed as it may have a significant impact on a comparison between different LF codecs. Very few in-depth comparisons on the effects of using existing LF representation have been reported. Therefore, using the guidelines from JPEG Pleno, this paper presents an exhaustive comparative analysis of these two LF data representation formats in terms of LF image coding efficiency, considering different color subsampling formats and bit depths. These comparisons are performed by testing different processing chains to encode and decode the LF images. Experimental results have shown that, in terms of coding efficiency for different color subsampling formats, the Lenslet LF data representation is more efficient when using YUV 4: 4: 4 with 10 bit/sample, while the 4D LF data representation is more efficient when using YUV 4: 2: 0 with 8 bit/sample. The "best" LF data represe

关键词： light field light field image coding light field Data Representation JPEG Pleno Objective Performance Assessment

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light field image coding Using High-Order Intrablock Prediction

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2017年第7期11卷 1120-1131页

作者： Monteiro, Ricardo J. S. Nunes, Paulo J. L. Rodrigues, Nuno M. M. Faria, Sergio M. M. Inst Telecomunicacoes P-1049001 Lisbon Portugal Univ Inst Lisbon P-1649026 Lisbon Portugal Univ Inst Lisbon Informat Sci & Technol Dept P-1649026 Lisbon Portugal Inst Telecomunicacoes P-2411901 Leiria Portugal Inst Politecn Leiria Escola Super Tecnol & Gestao P-2411901 Leiria Portugal

This paper proposes a two-stage high-order intra-block prediction method for light field image coding. This method exploits the spatial redundancy in lenslet light field images by predicting each image block, through a geometric transformation applied to a region of the causal encoded area. light field images comprise an array of microimages that are related by complex geometric transformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low-order translational prediction models. The two-stage nature of the proposed method allows us to choose the order of the prediction model most suitable for each block, ranging from pure translations to projective or bilinear transformations, optimized according to an appropriate rate-distortion criterion. The proposed higher order intrablock prediction approach was integrated into a high efficiency video coding (HEVC) codec and evaluated for both unfocused and focused light field camera models, using different resolutions and microlens arrays. Experimental results show consistent bitrate savings, which can go up to 12.62%, when compared to a lower order intrablock prediction solution and 49.82% when compared to HEVC still picture coding.

关键词： Geometric transformations HEVC high order intra block prediction light field image coding

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4D Epanechnikov Mixture Regression in LF image Compression

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年第6期32卷 3906-3922页

作者： Liu, Boning Zhao, Yan Jiang, Xiaomeng Wang, Shigang Wei, Jian Jilin Univ Coll Commun Engn Changchun 130012 Peoples R China Jilin Univ Coll Math Changchun 130012 Peoples R China

With the emergence of light field imaging in recent years, the compression of its elementary image array (EIA) has become a significant problem. Our coding framework includes modeling and reconstruction. For the modeling, the covariance-matrix form of the 4D Epanechnikov kernel (4D EK) and its correlated statistics were deduced to obtain the 4-D Epanechnikov mixture models (4-D EMMs). A 4D Epanechnikov mixture regression (4D EMR) was proposed based on this 4D EK, and a 4D adaptive model selection (4D AMLS) algorithm was designed to realize the optimal modeling for a pseudo video sequence (PVS) of the extracted key-EIA. A linear function based reconstruction (LFBR) was proposed based on the correlation between adjacent elementary images (EIs). The decoded images realized a clear outline reconstruction and superior coding efficiency compared to high-efficiency video coding (HEVC) and JPEG 2000 below approximately 0.05 bpp. This work realized an unprecedented theoretical application by (1) proposing the 4D Epanechnikov kernel theory, (2) exploiting the 4D Epanechnikov mixture regression and its application in the modeling of the pseudo video sequence of light field images, (3) using 4D adaptive model selection for the optimal number of models, and (4) employing a linear function-based reconstruction according to the content similarity.

关键词： image coding Kernel image reconstruction Adaptation models Transform coding Prediction algorithms Video sequences 4D Epanechnikov kernel 4D Epanechnikov mixture model 4D Epanechnikov mixture regression light field image coding Kernel method

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light field HEVC-BASED image coding USING LOCALLY LINEAR EMBEDDING AND SELF-SIMILARITY COMPENSATED PREDICTION

LIGHT FIELD HEVC-BASED IMAGE CODING USING LOCALLY LINEAR EMB...

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IEEE International Conference on Multimedia & Expo (ICME)

作者： Monteiro, Ricardo Lucas, Luis Conti, Caroline Nunes, Paulo Rodrigues, Nuno Faria, Sergio Pagliari, Carla da Silva, Eduardo Soares, Luis Instituto Telecomunicacoes Lisbon Portugal Inst Univ Lisboa ISCTE Lisbon Portugal Inst Pol Leiria ESTG Leiria Portugal Inst Mil Engn DEE Rio De Janeiro RJ Brazil Univ Fed Rio de Janeiro PEE COPPE DEK Poli BR-21941 Rio De Janeiro Brazil

ISBN: (纸本)9781509015528

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.

关键词： light field image coding self-similarity image prediction locally linear embedding HEVC

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