1,720,977 research outputs found
A differential motion estimation method for image interpolation in distributed video coding
Get PDFMotion estimation methods based on differential techniques proved to be very useful in the context of video analysis, but have a limited employment in classical video compression because, though accurate, the dense motion vector field they produce requires too much coding resource and computational effort. On the contrary, this kind of algorithm could be useful in the framework of distributed video coding (DVC). In this paper we propose a differential motion estimation algorithm which can run at the decoder in a DVC scheme, without requiring any increase in coding rate. This algorithm allows a performance improvement in image interpolation with respect to state-of-the-art algorithms. ©2009 IEEE
Side information refinement for long duration GOPs in DVC
No full textSide information generation is a critical step in distributed video coding systems. This is performed by using motion compensated temporal interpolation between two or more key frames (KFs). However, when the temporal distance between key frames increases (i.e. when the GOP size becomes large), the linear interpolation becomes less effective. In a previous work we showed that this problem can be mitigated by using high order interpolation. Now, in the case of long duration GOP, state-of-the-art algorithms propose a hierarchical algorithm for side information generation. By using this procedure, the quality of the central interpolated image in a GOP is consistently worse than images closer to the KFs. In this paper we propose a refinement of the central WZFs by higher order interpolation of the already decoded WZFs, that are closer to the WZF to be estimated. So we reduce the fluctuation of side information quality, with a beneficial impact on final rate-distortion characteristics of the system. The experimental results show an improvement on the SI up to 2.71 dB with respect the state-of-the-art and a global improvement of the PSNR on the decoded frames up to 0.71 dB and a bit rate reduction up to 15 %. ©2010 IEEE
Image interpolation with edge-preserving differential motion refinement
No full textMotion estimation (ME) methods based on differential techniques provide useful information for video analysis, and moreover it is relatively easy to embed into them regularity constraints enforcing for example, contour preservation. On the other hand, these techniques are rarely employed for video compression since, though accurate, the dense motion vector field (MVF) they produce requires too much coding resource and computational effort. However, this kind of algorithm could be useful in the framework of distributed video coding (DVC), where the motion vector are computed at the decoder side, so that no bit-rate is needed to transmit them. Moreover usually the decoder has enough computational power to face with the increased complexity of differential ME. In this paper we introduce a new image interpolation algorithm to be used in the context of DVC. This algorithm combines a popular DVC technique with differential ME. We adapt a pel-recursive differential ME algorithm to the DVC context; moreover we insert a regularity constraint which allows more consistent MVFs. The experimental results are encouraging: the quality of interpolated images is improved of up to 1.1 dB w.r.t. to state-of-the-art techniques. These results prove to be consistent when we use different GOP sizes. ©2009 IEEE
Depth-based multiview distributed video coding
No full textMultiview distributed video coding (DVC) has gained much attention in the last few years because of its potential in avoiding communication between cameras without decreasing the coding performance. However, the current results are not matching the expectations mainly due to the fact that some theoretical assumptions are not satisfied in the current implementations. For example, in distributed source coding the encoder must know the correlation between the sources, which cannot be achieved in the traditional DVC systems without having a communication between the cameras. In this work, we propose a novel multiview distributed video coding scheme in which the depth maps are used to estimate the way two views are correlated with no exchanges between the cameras. Only their relative positions are known. We design the complete scheme and further propose a rate allocation algorithm to efficiently share the bit budget between the different components of our scheme. Then, a rate allocation algorithm for depth maps is proposed in order to maximize the quality of synthesized virtual views. We show, through detailed experiments, that our scheme significantly outperforms the state-of-the-art DVC system
Image interpolation with dense disparity estimation in multiview distributed video coding
No full textThis paper deals with the side information (SI) gen- eration problem in multiview distributed video coding (MDVC). For inter-view interpolation, we propose a novel dense disparity estimation (DE) approach combined with a popular distributed video coding (DVC) technique. As disparity vectors are computed at the decoder side, and no coding rate is needed to transmit them, dense estimation techniques are made possible, leading to improved results without requiring high coding resources. Experimental results show that the proposed interpolation tech- nique can achieve up to 2.0 dB improvement in SI reconstruction performance, when compared to state-of-the-art DVC techniques. © 2009 IEEE
Fusion schemes for multiview distributed video coding
No full textDistributed video coding performances strongly depend on the side information quality, built at the decoder. In multi-view schemes, correlations in both time and view directions are exploited, obtaining in general two estimations that need to be merged. This step, called fusion, greatly affects the performance of the coding scheme; however, the existing methods do not achieve acceptable performances in all cases, especially when one of the estimations is not of good quality, since in this case they are not able to discard it. This paper provides a detailed review of existing fusion methods between temporal and inter-view side information, and proposes new promising techniques. Experimental results show that these methods have good performances in a variety of configurations. © EURASIP, 2009
A distributed video coding system for multi view video plus depth
No full textMulti-view video plus depth (MVD) is gathering huge attention, as witnessed by the recent standardization activity, since its rich information about the geometry of the scene allows high-quality synthesis of virtual viewpoints. Distributed video coding of such kind of content is a challenging problem whose solution could enable new services as interactive multi-view streaming. In this work we propose to exploit the geometrical information of the MVD format in order to estimate inter-view occlusions without communication among cameras. Experimental results show a bit rate reduction up to 77% for low bit rate w.r.t. state-of-the-art architectures. © 2013 IEEE
Evaluation of Side Information Effectiveness in Distributed Video Coding
No full textThe rate-distortion performance of a distributed video coding system strongly depends on the characteristics of the side information. One could naively think that the best side information is the one with the largest PSNR with respect to the original corresponding image. However, previous works have shown that this is not always the case and a reduction of the side information MSE does not always translate into better rate-distortion performance for the complete system. The scope of this paper is to explore a set of metrics other than the PSNR and explicitly designed to classify the side information with respect to its impact on the end-to-end compression performance. A first contribution is to define an experimental framework that can be used to meaningfully compare different metrics for side information evaluation. As a second contribution, our analysis allows to understand why in some cases PSNR-based metrics provide a fairly reliable estimation of the side information quality, while in other cases they do not. This analysis also allows us to introduce a set of new metrics that are better adapted for side information effectiveness evaluation, and that are based on a suitable power of the absolute difference between side information and the original image, or on the Hamming distance between the respective transform coefficients. Besides their theoretical interest, these new metrics can also improve the rate-distortion performance of some distributed video coding systems such as the hash-based ones. We observe improvement up to 74 % rate reduction in a simple study case.LTS
Key view selection in distributed multiview coding
No full textMultiview image and video systems with large number of views lead to new problems in data representation, transmission and user interaction. In order to reduce the data volumes, most distributed multiview coding schemes exploit the inter-view redundancies at the decoder side, using view synthesis from key views. In the situation where many views are considered, the two following questions become fundamental: i) how many key views have to be chosen for keeping a good reconstruction quality with reasonable coding cost? ii) where to place them optimally in the multiview sequences? We propose in this paper an algorithm for selecting the key views in a distributed multiview coding scheme. Based on a novel metric for the correlation between the views, we formulate an optimization problem for the positioning of the key views such that both the distortion of the reconstruction and the coding rate cost are effectively minimized. We then propose a new optimization strategy based on shortest path algorithm that permits to determine both the optimal number of key views and their positions in the image set. We experimentally validate our solution in a practical distributed multiview coding system and we show that considering the 3D scene geometry in the key view positioning brings significant rate-distortion improvements compared to distance-based key view selection as it is commonly done in the literature
Reference view selection in DIBR-based multiview coding
No full textAugmented 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 with traditional video services. The significant increase in 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 multiview 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 data set. In such coding schemes, the two following questions become fundamental: 1) how many reference views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key views in the multiview data set? 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 multiview coding scheme. We show that considering the 3D scene geometry in the reference view, positioning problem brings significant rate-distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras
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