Lossless contour coding using elastic curves in multiview video plus depth

Calemme, Marco; Cagnazzo, Marco; Pesquet‐Popescu, Béatrice

doi:10.1017/atsip.2014.20

Cited by 4 publications

(17 citation statements)

References 29 publications

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“…This paper addresses the issue of evaluating the effects of contour-preserving compression techniques on synthesized images by means of a subjective test. We compared, with subjective results and objective metrics, HEVC, the technique proposed in [6], and the presented simple technique NR. The positive impact of contour preserving depth coding was confirmed by our study.…”

Section: Discussionmentioning

confidence: 99%

“…The encoder will only have to send a value in [0, 1] to let the decoder identify this curve. The lossless coding of the contour is performed through an arithmetic coder, and the input symbol probability distribution is modified on the fly according to the elastic prediction [6].…”

Section: Coding Of Depth Mapsmentioning

confidence: 99%

“…A segmentation map of the scene with different objects can be coded with our lossless contour coding technique, and this map can be used in conjunction with an object-based coding technique to code the depth images. The method proposed in [6] relies on the SA (Shape Adaptive) Wavelet Transform [10], followed by SA SPIHT (Set Partitioning In Hierarchical Trees) [11], followed by an arithmetic coder for the SPIHT symbols (memoryless, without context). This provides an entirely Intra technique for the inner part of the objects.…”

Section: Coding Of Depth Mapsmentioning

confidence: 99%

“…In a previous work we proposed a technique using elastic deformation of curves to losslessly encode the object contours, and shape-adaptive wavelet to represent the inner parts of the objects [6]. In a practical bit-rate range, this technique proved to be competitive with HEVC [7], stateof-the-art for hybrid block-based coding techniques, in terms of objective quality metrics (PSNR and SSIM).…”

Section: Introductionmentioning

confidence: 99%

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Contour-Based Depth Coding: A Subjective Quality Assessment Study

Calemme¹,

Cagnazzo²,

Pesquet‐Popescu³

2015

2015 IEEE International Symposium on Multimedia (ISM)

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Multi-view video plus depth is emerging as the most flexible format for 3D video representation, as witnessed by the current standardization efforts by ISO and ITU. The depth information allows synthesizing virtual view points, and for its compression various techniques have been proposed. It is generally recognized that a high quality view rendering at the receiver side is possible only by preserving the contour information since distortions on edges during the encoding step would cause a sensible degradation on the synthesized view and on the 3D perception. As a consequence recent approaches include contour-based coding of depths. However, the impact of contour-preserving depth-coding on the perceived quality of synthesized images has not been conveniently studied. Therefore in this paper we make an investigation by means of a subjective study to better understand the limits and the potentialities of the different techniques.Our results show that the contour information is indeed relevant in the synthesis step: preserving the contours and coding coarsely the rest typically leads to images that users cannot tell apart from the reference ones, even at low bit rate. Moreover, our results show that objective metrics that are commonly used to evaluate synthesized images may have a low correlation coefficient with MOS rates and are in general not consistent across several techniques and contents.

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Section: Discussionmentioning

confidence: 99%

Section: Coding Of Depth Mapsmentioning

confidence: 99%

Section: Coding Of Depth Mapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contour-Based Depth Coding: A Subjective Quality Assessment Study

Calemme¹,

Cagnazzo²,

Pesquet‐Popescu³

2015

2015 IEEE International Symposium on Multimedia (ISM)

Self Cite

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“…2 for N pred = 1 and 2. We assume in the following that the depth maps are also coded, but at a sufficiently high quality to preserve the DIBR accuracy (e.g., by using contour preserving techniques [27], [28], [29]). At the decoder side, depth maps are only used to perform prediction of camera views (i.e., we do not consider virtual viewpoint in our framework).…”

Section: A Frameworkmentioning

confidence: 99%

Reference View Selection in DIBR-Based Multiview Coding

Maugey

Petrazzuoli

Frossard

et al. 2016

IEEE Trans. on Image Process.

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Abstract-Augmented reality, interactive navigation in 3D scenes, multiview video and other emerging multimedia applications require large sets of images hence larger data volumes and increased resources compared to traditional video services. The significant increase of the number of images in multiview systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multi view video compression strategies have been proposed recently. Most of them use the concept of reference or key views that are used to estimate other images when there is high correlation in the dataset. In such coding schemes, the two following questions become fundamental: i) how many reference views have to be chosen for keeping a good reconstruction quality under coding cost constraints? ii) where to place these key views in the multiview dataset? As these questions are largely overlooked in the literature, we study the reference view selection problem and propose an algorithm for the optimal selection of reference views in multiview coding systems. Based on a novel metric that measures the similarity between the views, we formulate an optimization problem for the positioning of the reference views such that both the distortion of the view reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of reference views and their positions in the image set. We experimentally validate our solution in a practical multiview distributed coding system and in the standardized 3D-HEVC multi view coding scheme. We show that considering the 3D scene geometry in the reference view positioning problem brings significant rate-distortion improvements and outperforms traditional coding strategy that simply selects key frames based on the distance between cameras.Index Terms-Multiview distributed coding, key view positioning, inter-view correlation, view synthesis, multiview image coding

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Depth map coding with elastic contours and 3D surface prediction

Calemme¹,

Zanuttigh²,

Milani³

et al. 2016

2016 IEEE International Conference on Image Processing (ICIP)

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Lossless contour coding using elastic curves in multiview video plus depth

Cited by 4 publications

References 29 publications

Contour-Based Depth Coding: A Subjective Quality Assessment Study

Contour-Based Depth Coding: A Subjective Quality Assessment Study

Reference View Selection in DIBR-Based Multiview Coding

Depth map coding with elastic contours and 3D surface prediction

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