Letteratura scientifica selezionata sul tema "Scalable video compression"

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Articoli di riviste sul tema "Scalable video compression"

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Secker, A., e D. Taubman. "Highly scalable video compression with scalable motion coding". IEEE Transactions on Image Processing 13, n. 8 (agosto 2004): 1029–41. http://dx.doi.org/10.1109/tip.2004.826089.

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Singh, A., J. Bove e V. Mkhael. "Multidimensional quantizers for scalable video compression". IEEE Journal on Selected Areas in Communications 11, n. 1 (1993): 36–45. http://dx.doi.org/10.1109/49.210542.

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Ke Shen e E. J. Delp. "Wavelet based rate scalable video compression". IEEE Transactions on Circuits and Systems for Video Technology 9, n. 1 (1999): 109–22. http://dx.doi.org/10.1109/76.744279.

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Illgner, K., e F. Muller. "Spatially scalable video compression employing resolution pyramids". IEEE Journal on Selected Areas in Communications 15, n. 9 (1997): 1688–703. http://dx.doi.org/10.1109/49.650043.

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Wai-Tian Tan e A. Zakhor. "Video multicast using layered FEC and scalable compression". IEEE Transactions on Circuits and Systems for Video Technology 11, n. 3 (marzo 2001): 373–86. http://dx.doi.org/10.1109/76.911162.

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Basha, Sardar N., e A. Rajesh. "Scalable Video Coding Using Accordion Discrete Wavelet Transform and Tucker Decomposition for Multimedia Applications". Journal of Computational and Theoretical Nanoscience 16, n. 2 (1 febbraio 2019): 601–8. http://dx.doi.org/10.1166/jctn.2019.7777.

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The digital world demands the transmission and storage of high quality video for streaming and broadcasting applications, the constraints are the network bandwidth and the memory of devices for the various multimedia and scientific applications, the video consists of spatial and temporal redundancies. The objective of any video compression algorithm is to eliminate the redundant information from the video signal during compression for effective transmission and storage. The correlation between the successive frames has not been exploited enough by the current compression algorithms. In this paper, a novel method for video compression is presented. The proposed model, applies the transformation on set of group of pictures (GOP). The high spatial correlation is achieved from the spatial and temporal redundancy of GOP by accordion representation and this helps to bypass the computationally demanding motion compensation step. The core idea of the proposed technique is to apply Tucker Decomposition (TD) on the Discrete Wavelet Transform (DWT) coefficients of the Accordion model of the GOP. We use DWT to separate the video in to different sub-images and TD to efficiently compact the energy of sub-images. The blocking artifacts will be considerably eliminated as the block size is huge. The proposed method attempts to reduce the spatial and temporal redundancies of the video signal to improve the compression ratio, computation time, and PSNR. The experimental results prove that the proposed method is efficient especially in high bit rate and with slow motion videos.
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Zhang, Mengmeng, Hongyun Lu e Zhi Liu. "Quality Scalability Compression on Single-Loop Solution in HEVC". Mathematical Problems in Engineering 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/149859.

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This paper proposes a quality scalable extension design for the upcoming high efficiency video coding (HEVC) standard. In the proposed design, the single-loop decoder solution is extended into the proposed scalable scenario. A novel interlayer intra/interprediction is added to reduce the amount of bits representation by exploiting the correlation between coding layers. The experimental results indicate that the average Bjøntegaard delta rate decrease of 20.50% can be gained compared with the simulcast encoding. The proposed technique achieved 47.98% Bjøntegaard delta rate reduction compared with the scalable video coding extension of the H.264/AVC. Consequently, significant rate savings confirm that the proposed method achieves better performance.
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Bhowmik, Deepayan, e Charith Abhayaratne. "2D+t Wavelet Domain Video Watermarking". Advances in Multimedia 2012 (2012): 1–19. http://dx.doi.org/10.1155/2012/973418.

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A novel watermarking framework for scalable coded video that improves the robustness against quality scalable compression is presented in this paper. Unlike the conventional spatial-domain (t + 2D) water-marking scheme where the motion compensated temporal filtering (MCTF) is performed on the spatial frame-wise video data to decompose the video, the proposed framework applies the MCTF in the wavelet domain (2D + t) to generate the coefficients to embed the watermark. Robustness performances against scalable content adaptation, such as Motion JPEG 2000, MC-EZBC, or H.264-SVC, are reviewed for various combinations of motion compensated 2D + t + 2D using the proposed framework. The MCTF is improved by modifying the update step to follow the motion trajectory in the hierarchical temporal decomposition by using direct motion vector fields in the update step and implied motion vectors in the prediction step. The results show smaller embedding distortion in terms of both peak signal to noise ratio and flickering metrics compared to frame-by-frame video watermarking while the robustness against scalable compression is improved by using 2D + t over the conventional t + 2D domain video watermarking, particularly for blind watermarking schemes where the motion is estimated from the watermarked video.
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Glenn, William E., John Marcinka e Robert Dhein. "Simple Scalable Video Compression Using 3-D Subband Coding". SMPTE Journal 105, n. 3 (marzo 1996): 140–43. http://dx.doi.org/10.5594/j04649.

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Li, Xin. "Scalable video compression via overcomplete motion compensated wavelet coding". Signal Processing: Image Communication 19, n. 7 (agosto 2004): 637–51. http://dx.doi.org/10.1016/j.image.2004.05.006.

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Tesi sul tema "Scalable video compression"

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Stampleman, Joseph Bruce. "Scalable video compression". Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/70216.

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Mehrseresht, Nagita Electrical Engineering &amp communication UNSW. "Adaptive techniques for scalable video compression". Awarded by:University of New South Wales. Electrical Engineering and communication, 2005. http://handle.unsw.edu.au/1959.4/20552.

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In this work we investigate adaptive techniques which can be used to improve the performance of highly scalable video compression schemes under resolution scaling. We propose novel content adaptive methods for motion compensated 3D discrete wavelet transformation (MC 3D-DWT) of video. The proposed methods overcome problems of ghosting and non-aligned aliasing artifacts, which can arise in regions of motion model failure, when the video is reconstructed at reduced temporal or spatial resolutions. We also study schemes which facilitate simultaneous scaling of compressed video bitstreams based on both constant bit-rate and constant distortion criteria, using simple and generic scaling operations. In regions where the motion model fails, the motion compensated temporal discrete wavelet transform (MC TDWT) causes ghosting artifacts under frame-rate scaling, due to temporal lowpass filtering along invalid motion trajectories. To avoid ghosting artifacts, we adaptively select between different lowpass filters, based on a local estimate of the motion modelling accuracy. Experimental results indicate that the proposed adaptive transform substantially removes ghosting artifacts while also preserving the high compression efficiency of the original MC TDWT. We also study the impact of various MC 3D-DWT structures on spatial scalability. Investigating the interaction between spatial aliasing, scalability and energy compaction shows that the t+2D structure essentially has higher compression efficiency. However, where the motion model fails, structures of this form cause non-aligned aliasing artifacts under spatial scaling. We propose novel adaptive schemes to continuously adapt the structure of MC 3D-DWT based on information available within the compressed bitstream. Experimental results indicate that the proposed adaptive structure preserves the high compression efficiency of the t+2D structure while also avoiding the appearance of non-aligned aliasing artifacts under spatial scaling. To provide simultaneous rate and distortion scaling, we study ???layered substream structure. Scaling based on distortion generates variable bit-rate traffic which satisfies the desired average bit-rate and is consistent with the requirements of leaky-bucket traffic models. We propose a novel method which also satisfies constraints on instantaneous bit-rate. This method overcomes the weakness of previous methods with small leaky-bucket buffer sizes. Simulation results indicate promising performance with both MC 3D-DWT interframe and JPEG2000 intraframe compression.
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Akhlaghian, Tab Fardin. "Multiresolution scalable image and video segmentation". Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060227.100704/index.html.

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Wang, Zhou. "Rate scalable foveated image and video communications /". Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3064684.

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Secker, Andrew J. Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Motion-adaptive transforms for highly scalable video compression". Awarded by:University of New South Wales. School of Electrical Engineering and Telecommunications, 2004. http://handle.unsw.edu.au/1959.4/33036.

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This thesis investigates motion-adaptive temporal transformations and motion parameter coding schemes, for highly scalable video compression. The first aspect of this work proposes a new framework for constructing temporal discrete wavelet transforms, based on motion-compensated lifting steps. The use of lifting preserves invertibility regardless of the selected motion model. By contrast, the invertibility requirement has restricted previous approaches to either block-based or global motion compensation. We show that the proposed framework effectively applies the temporal wavelet transform along the motion trajectories. Video sequences reconstructed at reduced frame-rates, from subsets of the compressed bitstream, demonstrate the visually pleasing properties expected from lowpass filtering along the motion trajectories. Experimental results demonstrate the effectiveness of temporal wavelet kernels other than the simple Haar. We also demonstrate the benefits of complex motion modelling, by using a deformable triangular mesh. These advances are either incompatible or diffcult to achieve with previously proposed strategies for scalable video compression. A second aspect of this work involves new methods for the representation, compression and rate allocation of the motion information. We first describe a compact representation for the various motion mappings associated with the proposed lifting transform. This representation significantly reduces the number of distinct motion fields that must be transmitted to the decoder. We also incorporate a rate scalable scheme for coding the motion parameters. This is achieved by constructing a set of quality layers for the motion information, in a manner similar to that used to construct the scalable sample representation. When the motion layers are truncated, the decoder receives a quantized version of the motion parameters used to code the sample data. A linear model is employed to quantify the effects of motion parameter quantization on the reconstructed video distortion. This allows the optimal trade-off between motion and subband sample bit-rates to be determined after the motion and sample data has been compressed. Two schemes are proposed to determine the optimal trade-off between motion and sample bit-rates. The first scheme employs a simple but effective brute force search approach. A second scheme explicitly utilizes the linear model, and yields comparable performance to the brute force scheme, with significantly less computational cost. The high performance of the second scheme also serves to reinforce the validity of the linear model itself. In comparison to existing scalable coding schemes, the proposed video coder achieves significantly higher compression performance, and motion scalability facilitates effcient compression even at low bit-rates. Experimental results show that the proposed scheme is also competitive with state-of-the-art non-scalable video coders.
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Li, Xue. "Scalable and adaptive video multicast over the internet". Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/8202.

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Leung, Raymond Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Scalable video compression with optimized visual performance and random accessibility". Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/24192.

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This thesis is concerned with maximizing the coding efficiency, random accessibility and visual performance of scalable compressed video. The unifying theme behind this work is the use of finely embedded localized coding structures, which govern the extent to which these goals may be jointly achieved. The first part focuses on scalable volumetric image compression. We investigate 3D transform and coding techniques which exploit inter-slice statistical redundancies without compromising slice accessibility. Our study shows that the motion-compensated temporal discrete wavelet transform (MC-TDWT) practically achieves an upper bound to the compression efficiency of slice transforms. From a video coding perspective, we find that most of the coding gain is attributed to offsetting the learning penalty in adaptive arithmetic coding through 3D code-block extension, rather than inter-frame context modelling. The second aspect of this thesis examines random accessibility. Accessibility refers to the ease with which a region of interest is accessed (subband samples needed for reconstruction are retrieved) from a compressed video bitstream, subject to spatiotemporal code-block constraints. We investigate the fundamental implications of motion compensation for random access efficiency and the compression performance of scalable interactive video. We demonstrate that inclusion of motion compensation operators within the lifting steps of a temporal subband transform incurs a random access penalty which depends on the characteristics of the motion field. The final aspect of this thesis aims to minimize the perceptual impact of visible distortion in scalable reconstructed video. We present a visual optimization strategy based on distortion scaling which raises the distortion-length slope of perceptually significant samples. This alters the codestream embedding order during post-compression rate-distortion optimization, thus allowing visually sensitive sites to be encoded with higher fidelity at a given bit-rate. For visual sensitivity analysis, we propose a contrast perception model that incorporates an adaptive masking slope. This versatile feature provides a context which models perceptual significance. It enables scene structures that otherwise suffer significant degradation to be preserved at lower bit-rates. The novelty in our approach derives from a set of "perceptual mappings" which account for quantization noise shaping effects induced by motion-compensated temporal synthesis. The proposed technique reduces wavelet compression artefacts and improves the perceptual quality of video.
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Lam, Sui Yuk. "Complexity optimization in H.264 and scalable extension /". View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?ECED%202008%20LAM.

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Lalgudi, Hariharan G., Michael W. Marcellin, Ali Bilgin e Mariappan S. Nadar. "SCALABLE LOW COMPLEXITY CODER FOR HIGH RESOLUTION AIRBORNE VIDEO". International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/605492.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada
Real-time transmission of airborne images to a ground station is highly desirable in many telemetering applications. Such transmission is often through an error prone, time varying wireless channel, possibly under jamming conditions. Hence, a fast, efficient, scalable, and error resilient image compression scheme is vital to realize the full potential of airborne reconnaisance. JPEG2000, the current international standard for image compression, offers most of these features. However, the computational complexity of JPEG2000 limits its use in some applications. Thus, we present a scalable low complexity coder (SLCC) that possesses many desirable features of JPEG2000, yet having high throughput.
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Danyali, Habibollah. "Highly scalable wavelet image and video coding for transmission over heterogeneous networks". Access electronically, 2004. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20041027.115306/index.html.

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Libri sul tema "Scalable video compression"

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Tudor, P. N. Digital video compression: Standardisation of scalable coding schemes. London: British Broadcasting Corporation. Research and Development Department, 1994.

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Rüfenacht, Dominic. Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2.

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Scalable computing and communications: Theory and practice. Hoboken, New Jersey: Wiley, 2013.

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Thie, Johnson. Optimal erasure protection assignment for scalable data: Protecting scalably compressed images and videos against erasure over packet-based networks. Köln: Lambert Academic Pub., 2009.

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Rüfenacht, Dominic. Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression. Springer, 2018.

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Rüfenacht, Dominic. Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression. Springer, 2019.

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Capitoli di libri sul tema "Scalable video compression"

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Rüfenacht, Dominic. "Scalable Image and Video Compression". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 7–36. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_2.

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Rüfenacht, Dominic. "Introduction". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 1–6. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_1.

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Rüfenacht, Dominic. "Temporal Frame Interpolation (TFI)". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 37–50. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_3.

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Rüfenacht, Dominic. "Motion-Discontinuity-Aided Motion Field Operations". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 51–74. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_4.

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Rüfenacht, Dominic. "Bidirectional Hierarchical Anchoring (BIHA) of Motion". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 75–102. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_5.

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Rüfenacht, Dominic. "Forward-Only Hierarchical Anchoring (FOHA) of Motion". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 103–37. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_6.

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Rüfenacht, Dominic. "Base-Anchored Motion (BAM)". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 139–65. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_7.

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Rüfenacht, Dominic. "Conclusions and Future Directions". In Novel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression, 167–72. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8225-2_8.

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Cai, Yu, Lin Mei, Dazhou Wu, Rui Zhao, Lili Jia e Weifei Wang. "Mobile Internet-Based Compression-Aware Scalable Video Coding - Rate Control for Enhancement Layers". In Communications in Computer and Information Science, 741–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31968-6_88.

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Solak, Serdar Burak, e Fabrice Labeau. "Green Video Compression for Portable and Low-Power Applications". In Sustainable ICTs and Management Systems for Green Computing, 325–49. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1839-8.ch014.

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This chapter presents recent advances in the implementation of video compression that allow for energy efficiency and management. Algorithmic complexity reduction and complexity management are key to the implementation of video compression in a green computing environment. The authors concentrate on low-power applications (such as smartphones or autonomous cameras), in which the ability to manage algorithmic complexity (and thus energy consumption) to match battery conditions and the priority of other tasks is one of the key enablers for reduced energy consumption. First, a study of the state-of-the-art video coding standard H.264/AVC and an analysis of its encoder complexity will be presented. Secondly, low complexity H.264/AVC encoder implementations will be explored in two categories as: Low Complexity Motion Estimation Algorithms and Low Complexity Mode Decision Algorithms. Later, a discussion of Complexity Scalable Encoding Algorithms that can adaptively adjust their computational complexities will follow. During the discussions, the authors will also introduce a novel framework for managing the complexity of an H.264/AVC encoder in a processor or power constrained environment as well as a complexity reduction tool. The chapter will conclude with a discussion about the future of sustainable green computing in video compression, followed by summary and concluding remarks.
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Atti di convegni sul tema "Scalable video compression"

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Kerofsky, L., A. Segall e Seung-Hwan Kim. "Color Gamut Scalable Video Coding". In 2013 Data Compression Conference (DCC). IEEE, 2013. http://dx.doi.org/10.1109/dcc.2013.29.

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Jianle Chen, K. Rapaka, Xiang Li, V. Seregin, Liwei Guo, M. Karczewicz, G. V. D. Auwera et al. "Scalable Video Coding Extension for HEVC". In 2013 Data Compression Conference (DCC). IEEE, 2013. http://dx.doi.org/10.1109/dcc.2013.27.

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Helle, P., H. Lakshman, M. Siekmann, J. Stegemann, T. Hinz, H. Schwarz, D. Marpe e T. Wiegand. "A Scalable Video Coding Extension of HEVC". In 2013 Data Compression Conference (DCC). IEEE, 2013. http://dx.doi.org/10.1109/dcc.2013.28.

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Bayrakeri, S., e R. M. Mersereau. "Temporally scalable video coding using nonlinear deinterlacing". In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582078.

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Wang, Qijun, Ruimin Hu e Zhongyuan Wang. "Spatially Scalable Video Coding Based on Hybrid Epitomic Resizing". In 2010 Data Compression Conference. IEEE, 2010. http://dx.doi.org/10.1109/dcc.2010.20.

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Khalifa, Othman O., Sinzobakwira Issa, R. F. Olanrewaju e El Mahdi A. Al Khazmi. "Development of a scalable video compression algorithm". In 2012 International Conference on Computer and Communication Engineering (ICCCE). IEEE, 2012. http://dx.doi.org/10.1109/iccce.2012.6271318.

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Somasundaram, Siva, e Koduvayur P. Subbalakshmi. "A novel 3D scalable video compression algorithm". In Electronic Imaging 2003, a cura di Bhaskaran Vasudev, T. Russell Hsing, Andrew G. Tescher e Touradj Ebrahimi. SPIE, 2003. http://dx.doi.org/10.1117/12.476718.

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Tang, Xin, Hongkai Xiong e Xiaoqian Jiang. "Multiscale Online Dictionary Learning for Quality Scalable Video Coding". In 2014 Data Compression Conference (DCC). IEEE, 2014. http://dx.doi.org/10.1109/dcc.2014.30.

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Chen, Jianle, Elena Alshina, Xiang Li, Marta Karczewicz e Alexander Alshin. "Resampling Process of the Scalable High Efficiency Video Coding". In 2015 Data Compression Conference (DCC). IEEE, 2015. http://dx.doi.org/10.1109/dcc.2015.60.

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Lan, Xuguang, Nanning Zheng, Jianru Xue, Weike Chen, Bin Wang, Wen Ma e Songlin Zhao. "A Peer-to-Peer Architecture Based on Scalable Video Coding". In 2008 Data Compression Conference DCC. IEEE, 2008. http://dx.doi.org/10.1109/dcc.2008.10.

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Rapporti di organizzazioni sul tema "Scalable video compression"

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Woods, John W. Scalable and Robust Video Compression. Fort Belvoir, VA: Defense Technical Information Center, dicembre 2000. http://dx.doi.org/10.21236/ada391136.

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