Novel solutions for side information generation and fusion in multiview DVC

Petrazzuoli, Giovanni; Cagnazzo, Marco; Pesquet‐Popescu, Béatrice

doi:10.1186/1687-6180-2013-154

Cited by 7 publications

(17 citation statements)

References 46 publications

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“…Motion and disparity compensated difference linear fusion (MDCD-Lin) is a multiview fusion technique [8] used as benchmark in [9,12]. The techniques presented in [9] are shown to perform either as well as MDCD-Lin or as well as the best single SI decoder.…”

Section: Benchmarks For Si Fusionmentioning

confidence: 99%

“…MVME demonstrates high performance in fast-motion sequences, but it is outperformed by motion compensation and interpolation techniques in slowmotion cases [11]. More recently [12], a modified version of the temporal motion estimation algorithm employed in DISCOVER [13] is proposed for inter-view SI generation. The key novelty is the penalization of small disparities, which characterizes background blocks.…”

Section: Inter-view Si Creationmentioning

confidence: 99%

“…A different approach for fusion in M-DVC is proposed in [9], where a past decoded WZ frame and its corresponding SI are used to train a support vector machine classifier, which is then used to perform the fusion task, classifying the reliability of each pixel in the SIs. In [12], the fusion is performed according to an occlusion map: temporal SI is used if pixels belonging to the left or right views are estimated to be occluded. In [12], adaptive validation is also introduced: for a small subset of the WZ frames, the parity bits are requested for correct inter-view and temporal SIs, introducing an overhead.…”

Section: Si Fusion Techniquesmentioning

confidence: 99%

“…In [12], the fusion is performed according to an occlusion map: temporal SI is used if pixels belonging to the left or right views are estimated to be occluded. In [12], adaptive validation is also introduced: for a small subset of the WZ frames, the parity bits are requested for correct inter-view and temporal SIs, introducing an overhead. If the two SIs require similar rates, the fused SI is chosen; otherwise, the single SI providing the lower rate is chosen.…”

Section: Si Fusion Techniquesmentioning

confidence: 99%

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A robust fusion method for multiview distributed video coding

Salmistraro

Ascenso²,

Brites³

et al. 2014

EURASIP J. Adv. Signal Process.

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Distributed video coding (DVC) is a coding paradigm which exploits the redundancy of the source (video) at the decoder side, as opposed to predictive coding, where the encoder leverages the redundancy. To exploit the correlation between views, multiview predictive video codecs require the encoder to have the various views available simultaneously. However, in multiview DVC (M-DVC), the decoder can still exploit the redundancy between views, avoiding the need for inter-camera communication. The key element of every DVC decoder is the side information (SI), which can be generated by leveraging intra-view or inter-view redundancy for multiview video data. In this paper, a novel learning-based fusion technique is proposed, which is able to robustly fuse an inter-view SI and an intra-view (temporal) SI. An inter-view SI generation method capable of identifying occluded areas is proposed and is coupled with a robust fusion system able to improve the quality of the fused SI along the decoding process through a learning process using already decoded data. We shall here take the approach to fuse the estimated distributions of the SIs as opposed to a conventional fusion algorithm based on the fusion of pixel values. The proposed solution is able to achieve gains up to 0.9 dB in Bjøntegaard difference when compared with the best-performing (in a RD sense) single SI DVC decoder, chosen as the best of an inter-view and a temporal SI-based decoder one.

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Section: Benchmarks For Si Fusionmentioning

confidence: 99%

Section: Inter-view Si Creationmentioning

confidence: 99%

Section: Si Fusion Techniquesmentioning

confidence: 99%

Section: Si Fusion Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

A robust fusion method for multiview distributed video coding

Salmistraro

Ascenso²,

Brites³

et al. 2014

EURASIP J. Adv. Signal Process.

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show abstract

“…The review of several important side information generation methods can be found in [8]. Additionally, new applications of DVC in [9,10] are inspired with these investigations.…”

Section: Introductionmentioning

confidence: 99%

Distributed video coding with block mode decision to reduce temporal flickering

Lee

Chiang

Tsai

et al. 2013

EURASIP J. Adv. Signal Process.

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The common distributed video coding (DVC) systems treat input video frames group by group. In each group of pictures (GOP), usually the first frame, called key frame, is intra-coded and the others are Wyner-Ziv (WZ)-coded. This GOP coding structure presents a fixed and inefficient coding mode switch (key or WZ) at group boundaries, thus preventing a DVC system from adapting the rate-distortion (R-D) performance to varying video content. In this work, a structure of temporal group of blocks (TGOB) with dynamic coding mode (key/WZ) decision is presented. This dynamic TGOB coding architecture determines each image block to be a key block or a WZ block based on spatiotemporal image analysis, resulting in a mode switch of fine granularity in both the spatial and temporal domains. As a consequence, not only the overall coding efficiency is improved, but also the temporal flickering artifacts for the reconstructed video are reduced substantially. Experimental results show that our proposed DVC scheme with block mode decision achieves up to 2.85 dB of quality gain and also up to 51% of temporal flickering reduction, compared to the well-known DISCOVER system.

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Image Fusion Techniques: A Survey

Kaur

Koundal

Kadyan

2021

Arch Computat Methods Eng

224

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The necessity of image fusion is growing in recently in image processing applications due to the tremendous amount of acquisition systems. Fusion of images is defined as an alignment of noteworthy Information from diverse sensors using various mathematical models to generate a single compound image. The fusion of images is used for integrating the complementary multi-temporal, multi-view and multi-sensor Information into a single image with improved image quality and by keeping the integrity of important features. It is considered as a vital pre-processing phase for several applications such as robot vision, aerial, satellite imaging, medical imaging, and a robot or vehicle guidance. In this paper, various state-of-art image fusion methods of diverse levels with their pros and cons, various spatial and transform based method with quality metrics and their applications in different domains have been discussed. Finally, this review has concluded various future directions for different applications of image fusion.

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Novel solutions for side information generation and fusion in multiview DVC

Cited by 7 publications

References 46 publications

A robust fusion method for multiview distributed video coding

A robust fusion method for multiview distributed video coding

Distributed video coding with block mode decision to reduce temporal flickering

Image Fusion Techniques: A Survey

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