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Karczewicz M.,Qualcomm | Ye Y.,InterDigital Communications | Auyeung C.,Sony Electronics Inc.
Data Compression Conference Proceedings | Year: 2015

SHVC is the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC). Color Gamut Scalability (CGS) refers to a scalable use case in which base layer and enhancement layer have different color gamuts. In this case, special inter-layer prediction is needed to improve coding efficiency in SHVC. In this paper, a solution based on asymmetric 3D lookup table is presented for color gamut scalability. Compared to SHVC without CGS coding tool, the proposed solution provides 9.6%-16.1% overall luma BD-rate reduction in different test cases. © 2015 IEEE. Source

Maani E.,Sony Electronics Inc. | Chen Z.,Northwestern University | Katsaggelos A.K.,Northwestern University
Signal Processing: Image Communication | Year: 2012

We consider the problem of foresighted multimedia resource reciprocation in peer-to-peer (P2P) networks, which consist of rational peers aiming at maximizing their individual utilities. We introduce an artificial currency (credit) to take into account the characteristics of different parts of the video signal. The resource reciprocation with the proposed credit metric can be formulated as a stochastic game, in which the peers determine their optimal strategies using Markov Decision Process (MDP) framework. The introduced framework can be applied to the general video coding, and in particular, is suitable for the scalable video where various parts of the encoded bit stream have significantly different importance for the video quality. © 2012 Elsevier B.V. All rights reserved. Source

Liu W.,University of Missouri | Liu W.,Sony Electronics Inc. | Dong L.,Partek, Inc. | Zeng W.,University of Missouri
IEEE Transactions on Circuits and Systems for Video Technology | Year: 2010

During the past ten years, Wyner-Ziv video coding (WZVC) has gained a lot of research interests because of its unique characteristics of simple encoding, complex decoding. However, the performance gap between WZVC and conventional video coding has never been closed to the point promised by the information theory. In this paper, we illustrate the chicken-and-egg dilemma encountered in WZVC: high-efficiency WZVC requires good estimation of side information (SI); however, good SI estimation is not possible for the decoder without access to the decoded current frame. To resolve such a dilemma, we present and advocate a framework that explores an important concept of decoder-side progressive-learning. More specifically, a decoder-side multi-resolution motion refinement (MRMR) scheme is proposed, where the decoder is able to learn from the already-decoded lower-resolution data to refine the motion estimation (ME), which in turn greatly improves the SI quality as well as the coding efficiency for the higher resolution data. Theoretical analysis shows that at high rates, decoder-side MRMR outperforms motion extrapolation by as much as 5 dB, while falling behind conventional encoder-side inter-frame ME by only about 1.5 dB. In addition, since decoder-side ME does not suffer from the bit-rate overhead in transmitting the motion information, further performance gain can be achieved for decoder-side MRMR by incorporating fractional-pel motion search, block matching with smaller block sizes, and multiple hypothesis prediction. We also present a practical WZVC implementation with MRMR, which shows comparable coding performance as H.264 at very high bit-rates. © 2006 IEEE. Source

Narayanaswamy A.,Rensselaer Polytechnic Institute | Dwarakapuram S.,Rensselaer Polytechnic Institute | Dwarakapuram S.,Sony Electronics Inc. | Bjornsson C.S.,Rensselaer Polytechnic Institute | And 3 more authors.
IEEE Transactions on Medical Imaging | Year: 2010

This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8 speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.11.6) voxels per mesh face for peak signal-to-noise ratios from (11028 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively. © 2010 IEEE. Source

Zhao W.,Sony Electronics Inc. | Xie J.,University of North Carolina at Charlotte
IEEE Transactions on Parallel and Distributed Systems | Year: 2013

Wireless mesh networks (WMNs) have been deployed in many areas. There is an increasing demand for supporting a large number of mobile users in WMNs. As one of the key components in mobility management support, location management serves the purpose of tracking mobile users and locating them prior to establishing new communications. Previous dynamic location management schemes proposed for cellular and wireless local area networks (WLANs) cannot be directly applied to WMNs due to the existence of multihop wireless links in WMNs. Moreover, new design challenges arise when applying location management for silently roaming mobile users in the mesh backbone. Considering the number of wireless hops, an important factor affecting the performance of WMNs, we propose a DoMaIN framework that can help mobile users to decide whether an intra- or intergateway location update (LU) is needed to ensure the best location management performance (i.e., packet delivery) among dynamic location management solutions. In addition, by dynamically guiding mobile users to perform LU to a desirable location entity, the proposed DoMaIN framework can minimize the location management protocol overhead in terms of LU overhead in the mesh backbone. Furthermore, DoMaIN brings extra benefits for supporting a dynamic hop-based LU triggering method that is different from previous dynamic LU triggering schemes proposed for cellular networks and WLANs. We evaluate the performance of DoMaIN in different case studies using OPNET simulations. Comprehensive simulation results demonstrate that DoMaIN outperforms other location management schemes and is a satisfactory location management solution for a large number of mobile users silently and arbitrarily roaming under the wireless mesh backbone. © 1990-2012 IEEE. Source

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