Готові списки джерел за темами / Video compression

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Добірка наукової літератури з теми "Video compression"

Автор: Grafiati
Опубліковано: 4 червня 2021
Оновлено: 30 липня 2024

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Статті в журналах з теми "Video compression"

1

Rajasekhar, H., and B. Prabhakara Rao. "An Efficient Video Compression Technique Using Watershed Algorithm and JPEG-LS Encoding." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 6671–79. http://dx.doi.org/10.1166/jctn.2016.5613.

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Анотація:
In the previous video compression method, the videos were segmented by using the novel motion estimation algorithm with aid of watershed method. But, the compression ratio (CR) of compression with novel motion estimation algorithm was not giving an adequate result. Moreover this methods performance is needed to be improved in the encoding and decoding processes. Because most of the video compression methods have utilized encoding techniques like JPEG, Run Length, Huffman coding and LSK encoding. The improvement of the encoding techniques in the compression process will improve the compression result. Hence, to overcome these drawbacks, we intended to propose a new video compression method with renowned encoding technique. In this proposed video compression method, the input video frames motion vectors are estimated by applying watershed and ARS-ST (Adaptive Rood Search with Spatio-Temporal) algorithms. After that, the vector blocks which have high difference value are encoded by using the JPEG-LS encoder. JPEG-LS have excellent coding and computational efficiency, and it outperforms JPEG2000 and many other image compression methods. This algorithm is of relatively low complexity, low storage requirement and its compression capability is efficient enough. To get the compressed video, the encoded blocks are subsequently decoded by JPEG-LS. The implementation result shows the effectiveness of proposed method, in compressing more number of videos. The performance of our proposed video compression method is evaluated by comparing the result of proposed method with the existing video compression techniques. The comparison result shows that our proposed method acquires high-quality compression ratio and PSNR for the number of testing videos than the existing techniques.
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2

Mishra, Amit Kumar. "Versatile Video Coding (VVC) Standard: Overview and Applications." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, no. 2 (September 10, 2019): 975–81. http://dx.doi.org/10.17762/turcomat.v10i2.13578.

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Information security includes picture and video compression and encryption since compressed data is more secure than uncompressed imagery. Another point is that handling data of smaller sizes is simple. Therefore, efficient, secure, and simple data transport methods are created through effective data compression technology. Consequently, there are two different sorts of compression algorithm techniques: lossy compressions and lossless compressions. Any type of data format, including text, audio, video, and picture files, may leverage these technologies. In this procedure, the Least Significant Bit technique is used to encrypt each frame of the video file format to be able to increase security. The primary goals of this procedure are to safeguard the data by encrypting the frames and compressing the video file. Using PSNR to enhance process throughput would also enhance data transmission security while reducing data loss.
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3

Strachan, David, Margarida DeBruin, and Robert Marhong. "Video Compression." SMPTE Journal 105, no. 2 (February 1996): 68–73. http://dx.doi.org/10.5594/j04666.

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4

Et. al., G. Megala,. "State-Of-The-Art In Video Processing: Compression, Optimization And Retrieval." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (April 11, 2021): 1256–72. http://dx.doi.org/10.17762/turcomat.v12i5.1793.

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Анотація:
Video compression plays a vital role in the modern social media networking with plethora of multimedia applications. It empowers transmission medium to competently transfer videos and enable resources to store the video efficiently. Nowadays high-resolution video data are transferred through the communication channel having high bit rate in order to send multiple compressed videos. There are many advances in transmission ability, efficient storage ways of these compressed video where compression is the primary task involved in multimedia services. This paper summarizes the compression standards, describes the main concepts involved in video coding. Video compression performs conversion of large raw bits of video sequence into a small compact one, achieving high compression ratio with good video perceptual quality. Removing redundant information is the main task in the video sequence compression. A survey on various block matching algorithms, quantization and entropy coding are focused. It is found that many of the methods having computational complexities needs improvement with optimization.
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5

Mohammed, Dhrgham Hani, and Laith Ali Abdul-Rahaim. "A Proposed of Multimedia Compression System Using Three - Dimensional Transformation." Webology 18, SI05 (October 30, 2021): 816–31. http://dx.doi.org/10.14704/web/v18si05/web18264.

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Video compression has become especially important nowadays with the increase of data transmitted over transmission channels, the reducing the size of the videos must be done without affecting the quality of the video. This process is done by cutting the video thread into frames of specific lengths and converting them into a three-dimensional matrix. The proposed compression scheme uses the traditional red-green-blue color space representation and applies a three-dimensional discrete Fourier transform (3D-DFT) or three-dimensional discrete wavelet transform (3D-DWT) to the signal matrix after converted the video stream to three-dimensional matrices. The resulting coefficients from the transformation are encoded using the EZW encoder algorithm. Three main criteria by which the performance of the proposed video compression system will be tested; Compression ratio (CR), peak signal-to-noise ratio (PSNR) and processing time (PT). Experiments showed high compression efficiency for videos using the proposed technique with the required bit rate, the best bit rate for traditional video compression. 3D discrete wavelet conversion has a high frame rate with natural spatial resolution and scalability through visual and spatial resolution Beside the quality and other advantages when compared to current conventional systems in complexity, low power, high throughput, low latency and minimum the storage requirements. All proposed systems implement using MATLAB R2020b.
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6

Lu, Ming, Zhihao Duan, Fengqing Zhu, and Zhan Ma. "Deep Hierarchical Video Compression." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 8 (March 24, 2024): 8859–67. http://dx.doi.org/10.1609/aaai.v38i8.28733.

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Recently, probabilistic predictive coding that directly models the conditional distribution of latent features across successive frames for temporal redundancy removal has yielded promising results. Existing methods using a single-scale Variational AutoEncoder (VAE) must devise complex networks for conditional probability estimation in latent space, neglecting multiscale characteristics of video frames. Instead, this work proposes hierarchical probabilistic predictive coding, for which hierarchal VAEs are carefully designed to characterize multiscale latent features as a family of flexible priors and posteriors to predict the probabilities of future frames. Under such a hierarchical structure, lightweight networks are sufficient for prediction. The proposed method outperforms representative learned video compression models on common testing videos and demonstrates computational friendliness with much less memory footprint and faster encoding/decoding. Extensive experiments on adaptation to temporal patterns also indicate the better generalization of our hierarchical predictive mechanism. Furthermore, our solution is the first to enable progressive decoding that is favored in networked video applications with packet loss.
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7

P, Srividya. "Optimization of Lossless Compression Algorithms using Multithreading." Journal of Information Technology and Sciences 9, no. 1 (March 2, 2023): 36–42. http://dx.doi.org/10.46610/joits.2022.v09i01.005.

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Анотація:
The process of reducing the number of bits required to characterize data is referred to as compression. The advantages of compression include a reduction in the time taken to transfer data from one point to another, and a reduction in the cost required for the storage space and network bandwidth. There are two types of compression algorithms namely lossy compression algorithm and lossless compression algorithm. Lossy algorithms find utility in compressing audio and video signals whereas lossless algorithms are used in compressing text messages. The advent of the internet and its worldwide usage has not only raised the utility but also the storage of text, audio and video files. These multimedia files demand more storage space as compared to traditional files. This has given rise to the requirement for an efficient compression algorithm. There is a considerable improvement in the computing performance of the machines due to the advent of the multi-core processor. However, this multi-core architecture is not used by compression algorithms. This paper shows the implementation of lossless compression algorithms namely the Lempel-Ziv-Markov Algorithm, BZip2 and ZLIB algorithms using the concept of multithreading. The results obtained prove that the ZLIB algorithm proves to be more efficient in terms of the time taken to compress and decompress the text. The comparison is done for both compressions without multithreading and compression with multi-threading.
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8

P, Srividya. "Optimization of Lossless Compression Algorithms using Multithreading." Journal of Information Technology and Sciences 9, no. 1 (March 1, 2023): 36–42. http://dx.doi.org/10.46610/joits.2023.v09i01.005.

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Анотація:
The process of reducing the number of bits required to characterize data is referred to as compression. The advantages of compression include a reduction in the time taken to transfer data from one point to another, and a reduction in the cost required for the storage space and network bandwidth. There are two types of compression algorithms namely lossy compression algorithm and lossless compression algorithm. Lossy algorithms find utility in compressing audio and video signals whereas lossless algorithms are used in compressing text messages. The advent of the internet and its worldwide usage has not only raised the utility but also the storage of text, audio and video files. These multimedia files demand more storage space as compared to traditional files. This has given rise to the requirement for an efficient compression algorithm. There is a considerable improvement in the computing performance of the machines due to the advent of the multi-core processor. However, this multi-core architecture is not used by compression algorithms. This paper shows the implementation of lossless compression algorithms namely the Lempel-Ziv-Markov Algorithm, BZip2 and ZLIB algorithms using the concept of multithreading. The results obtained prove that the ZLIB algorithm proves to be more efficient in terms of the time taken to compress and decompress the text. The comparison is done for both compressions without multithreading and compression with multi-threading.
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9

Flierl, Markus, and Bernd Girod. "Multiview Video Compression." IEEE Signal Processing Magazine 24, no. 99 (2007): 66–76. http://dx.doi.org/10.1109/msp.2007.4317465.

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Flierl, Markus, and Bernd Girod. "Multiview Video Compression." IEEE Signal Processing Magazine 24, no. 6 (November 2007): 66–76. http://dx.doi.org/10.1109/msp.2007.905699.

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Дисертації з теми "Video compression"

1

Zhang, Fan. "Parametric video compression." Thesis, University of Bristol, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.574421.

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Анотація:
Advances in communication and compression technologies have facilitated the transmission of high quality video content across a broad range of net- works to numerous terminal types. Challenges for video coding continue to increase due to the demands on bandwidth from increased frame rates, higher resolutions and complex formats. In most cases, the target of any video coding algorithm is, for a given bitrate, to provide the best subjective quality rather than simply produce the most similar pictures to the originals. Based on this premise, texture analysis and synthesis can be utilised to provide higher performance video codecs. This thesis describes a novel means of parametric video compression based on texture warping and synthesis. Instead of encoding whole images or prediction residuals after translational motion estimation, this approach employs a perspective motion model to warp static textures and utilises texture synthesis to create dynamic textures. Texture regions are segmented using features derived from the com- plex wavelet transform and further classified according to their spatial and temporal characteristics. A compatible artefact-based video metric (AVM) has been designed to evaluate the quality of the reconstructed video. Its enhanced version is further developed as a generic perception-based video metric offering improved performance in correlation with subjective opinions. It is unique in being able to assess both synthesised and conventionally coded content. The AVM is accordingly employed in the coding loop to prevent warping and synthesis artefacts, and a local RQO strategy is then developed based on it to make a trade-off between waveform coding and texture warping/synthesis. In addition, these parametric texture models have been integrated into an H.264 video coding framework whose results show significant coding efficiency improvement, up to 60% bitrate savings over H.264/ AVC, on diverse video content.
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2

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

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Cilke, Tom. "Video Compression Techniques." International Foundation for Telemetering, 1988. http://hdl.handle.net/10150/615075.

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International Telemetering Conference Proceedings / October 17-20, 1988 / Riviera Hotel, Las Vegas, Nevada
This paper will attempt to present algorithms commonly used for video compression, and their effectiveness in aerospace applications where size, weight, and power are of prime importance. These techniques will include samples of one-, two-, and three-dimensional algorithms. Implementation of these algorithms into usable hardware is also explored but limited to monochrome video only.
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4

Bordes, Philippe. "Adapting video compression to new formats." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S003/document.

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Les nouvelles techniques de compression vidéo doivent intégrer un haut niveau d'adaptabilité, à la fois en terme de bande passante réseau, de scalabilité des formats (taille d'images, espace de couleur…) et de compatibilité avec l'existant. Dans ce contexte, cette thèse regroupe des études menées en lien avec le standard HEVC. Dans une première partie, plusieurs adaptations qui exploitent les propriétés du signal et qui sont mises en place lors de la création du bit-stream sont explorées. L'étude d'un nouveau partitionnement des images pour mieux s'ajuster aux frontières réelles du mouvement permet des gains significatifs. Ce principe est étendu à la modélisation long-terme du mouvement à l'aide de trajectoires. Nous montrons que l'on peut aussi exploiter la corrélation inter-composantes des images et compenser les variations de luminance inter-images pour augmenter l'efficacité de la compression. Dans une seconde partie, des adaptations réalisées sur des flux vidéo compressés existants et qui s'appuient sur des propriétés de flexibilité intrinsèque de certains bit-streams sont investiguées. En particulier, un nouveau type de codage scalable qui supporte des espaces de couleur différents est proposé. De ces travaux, nous dérivons des metadata et un modèle associé pour opérer un remapping couleur générique des images. Le stream-switching est aussi exploré comme une application particulière du codage scalable. Plusieurs de ces techniques ont été proposées à MPEG. Certaines ont été adoptées dans le standard HEVC et aussi dans la nouvelle norme UHD Blu-ray Disc. Nous avons investigué des méthodes variées pour adapter le codage de la vidéo aux différentes conditions de distribution et aux spécificités de certains contenus. Suivant les scénarios, on peut sélectionner et combiner plusieurs d'entre elles pour répondre au mieux aux besoins des applications
The new video codecs should be designed with an high level of adaptability in terms of network bandwidth, format scalability (size, color space…) and backward compatibility. This thesis was made in this context and within the scope of the HEVC standard development. In a first part, several Video Coding adaptations that exploit the signal properties and which take place at the bit-stream creation are explored. The study of improved frame partitioning for inter prediction allows better fitting the actual motion frontiers and shows significant gains. This principle is further extended to long-term motion modeling with trajectories. We also show how the cross-component correlation statistics and the luminance change between pictures can be exploited to increase the coding efficiency. In a second part, post-creation stream adaptations relying on intrinsic stream flexibility are investigated. In particular, a new color gamut scalability scheme addressing color space adaptation is proposed. From this work, we derive color remapping metadata and an associated model to provide low complexity and general purpose color remapping feature. We also explore the adaptive resolution coding and how to extend scalable codec to stream-switching applications. Several of the described techniques have been proposed to MPEG. Some of them have been adopted in the HEVC standard and in the UHD Blu-ray Disc. Various techniques for adapting the video compression to the content characteristics and to the distribution use cases have been considered. They can be selected or combined together depending on the applications requirements
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Rambaruth, Ratna. "Region-based video compression." Thesis, University of Surrey, 1999. http://epubs.surrey.ac.uk/843377/.

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First generation image coding standards are now well-established and coders based on these standards are commercially available. However, for emerging applications, good quality at even lower bitrates is required. Ways of exploiting higher level visual information are currently being explored by the research community in order to achieve high compression. Unfortunately very high level approaches are bound to be restrictive as they are highly dependent on the accuracy of lower-level vision operations. Region-based coding only relies on mid-level image processing and thus is viewed as a promising strategy. In this work, substantial advances to the field of region-based video compression are made by considering the complete scheme. Thus, improvements to the failure regions coding and the motion compensation components have been devised. The failure region coding component was improved by predicting the texture inside the failure region from the neighbourhood of the region. A significant gain over widely used techniques such as the SA-DCT was obtained. The accuracy of the motion compensation component was increased by keeping an accurate internal representation for each region both at the encoder and the decoder side. The proposed region-based coding system is also evaluated against other systems, including the MPEG4 codec which has been recently approved by the MPEG community.
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6

Stephens, Charles R. "Video Compression Standardization Issues." International Foundation for Telemetering, 1988. http://hdl.handle.net/10150/615077.

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Анотація:
International Telemetering Conference Proceedings / October 17-20, 1988 / Riviera Hotel, Las Vegas, Nevada
This paper discusses the development of a standard for compressed digital video. The benefits and applications of compressed digital video are reviewed, and some examples of compression techniques are presented. A hardware implementation of a differential pulse code modulation approach is examined.
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Subramanian, Vivek. "Content-aware Video Compression." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254394.

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In a video there are certain regions in the image that viewers focus on more than others, which are called the salient regions or Regions­Of-Interest (ROI). This thesis aims to improve the perceived quality of videos by improving the quality of these ROis while degrading the quality of the other non-ROI regions of a frame to keep the same bitrate as would have been the case otherwise. This improvement is achieved by using saliency maps generated using an eye tracker or a deep neural network and providing this information to a modified video encoder. In this thesis the open source x264 encoder was chosen to make use of this information. The effects of ROI encoding are studied for high quality 720p videos by encoding them at low bitrates. The results indicate that ROI encoding can improve subjective video quality when carefully applied.
I en video £inns <let vissa delar av bilden som tittarna fokuserar mer pa an andra, och dessa kallas Region of Interest". Malet med den har upp­satsen ar att hoja den av tittaren upplevda videokvaliteten genom att minska kompressionsgraden ( och darmed hoja kvaliteten) i de iogon­fallande delarna av bilden, samtid som man hojer kompressionsgra­den i ovriga delar sa att bitraten blir den samma som innan andring­en. Den har forbattringen gors genom att anvanda Saliency Mapsss­om visar de iogonfallande delarna for varje bildruta. Dessa Saliency Maps"har antingen detekterats med hjalp av en Eye Tracker eller sa har de raknats fram av ett Neuralt Natverk. Informationen anvands sedan i en modifierad version av den oppna codecen x264 enligt en egen­designad algoritm. Effekten av forandringen har studerats genom att koda hogkvalitativa kallfiler vid lag bitrate. Resultaten indikerar att denna metod kan forbattra den upplevda kvaliteten av en video om den appliceras med ratt styrka.
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8

Yap, S. Y. "SoC architectures for video compression." Thesis, Queen's University Belfast, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.411805.

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Honoré, Francis. "A concurrent video compression system." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/37997.

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Mazhar, Ahmad Abdel Jabbar Ahmad. "Efficient compression of synthetic video." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/9019.

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Streaming of on-line gaming video is a challenging problem because of the enormous amounts of video data that need to be sent during game playing, especially within the limitations of uplink capabilities. The encoding complexity is also a challenge because of the time delay while on-line gamers are communicating. The main goal of this research study is to propose an enhanced on-line game video streaming system. First, the most common video coding techniques have been evaluated. The evaluation study considers objective and subjective metrics. Three widespread video coding techniques are selected and evaluated in the study; H.264, MPEG-4 Visual and VP- 8. Diverse types of video sequences were used with different frame rates and resolutions. The effects of changing frame rate and resolution on compression efficiency and viewers' satisfaction are also presented. Results showed that the compression process and perceptual satisfaction are severely affected by the nature of the compressed sequence. As a result, H.264 showed higher compression efficiency for synthetic sequences and outperformed other codecs in the subjective evaluation tests. Second, a fast inter prediction technique to speed up the encoding process of H.264 has been devised. The on-line game streaming service is a real time application, thus, compression complexity significantly affects the whole process of on-line streaming. H.264 has been recommended for synthetic video coding by our results gained in codecs comparative studies. However, it still suffers from high encoding complexity; thus a low complexity coding algorithm is presented as fast inter coding model with reference management technique. The proposed algorithm was compared to a state of the art method, the results showing better achievement in time and bit rate reduction with negligible loss of fidelity. Third, recommendations on tradeoff between frame rates and resolution within given uplink capabilities are provided for H.264 video coding. The recommended tradeoffs are offered as a result of extensive experiments using Double Stimulus Impairment Scale (DSIS) subjective evaluation metric. Experiments showed that viewers' satisfaction is profoundly affected by varying frame rates and resolutions. In addition, increasing frame rate or frame resolution does not always guarantee improved increments of perceptual quality. As a result, tradeoffs are recommended to compromise between frame rate and resolution within a given bit rate to guarantee the highest user satisfaction. For system completeness and to facilitate the implementation of the proposed techniques, an efficient game video streaming management system is proposed. Compared to existing on-line live video service systems for games, the proposed system provides improved coding efficiency, complexity reduction and better user satisfaction.
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Книги з теми "Video compression"

1

Beach, Andy. Video compression. Berkeley, Calif: Peachpit, 2007.

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Beach, Andy. Video compression. Berkeley, Calif: Peachpit, 2007.

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3

Punchihewa, Amal. Video compression. Rijeka, Croatia: InTech, 2012.

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4

Effelsberg, Wolfgang. Video compression techniques. Heidelberg, Germany: dpunkt-Verlag, 1998.

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5

Peter, Symes, ed. Digital video compression. New York: McGraw-Hill, 2004.

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6

Bhojani, Dhaval R., Vedvyas J. Dwivedi, and Rohit M. Thanki. Hybrid Video Compression Standard. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0245-3.

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Mitchell, Joan L., William B. Pennebaker, Chad E. Fogg, and Didier J. LeGall, eds. MPEG Video Compression Standard. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-4587-7.

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Mitchell, Joan L., William B. Pennebaker, Chad E. Fogg, and Didier J. LeGall. MPEG Video Compression Standard. New York, NY: Springer US, 1996. http://dx.doi.org/10.1007/b115884.

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L, Mitchell Joan, ed. MPEG video: Compression standard. New York: Chapman & Hall, 1996.

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10

Wu, Chwan-Hwa. Techniques for video compression. Auburn, Al: Auburn University, 1995.

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Частини книг з теми "Video compression"

1

Salomon, David. "Video Compression." In Data Compression, 581–630. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-86092-8_7.

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Janus, Scott. "Video Compression." In Handbook of Visual Display Technology, 425–41. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-14346-0_24.

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Chen, Yu-Han, and Liang-Gee Chen. "Video Compression." In Handbook of Signal Processing Systems, 49–67. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6859-2_2.

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Janus, Scott. "Video Compression." In Handbook of Visual Display Technology, 1–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-35947-7_24-2.

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Salomon, David, and Giovanni Motta. "Video Compression." In Handbook of Data Compression, 855–952. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-903-9_9.

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Janus, Scott. "Video Compression." In Handbook of Visual Display Technology, 287–300. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-79567-4_24.

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Chen, Yu-Han, and Liang-Gee Chen. "Video Compression." In Handbook of Signal Processing Systems, 103–21. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6345-1_5.

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Salomon, David. "Video Compression." In A Guide to Data Compression Methods, 227–39. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21708-6_6.

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Pereira, Rafael Silva, and Karin K. Breitman. "Video Compression." In Video Processing in the Cloud, 13–21. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2137-4_3.

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Sun, Lingfen, Is-Haka Mkwawa, Emmanuel Jammeh, and Emmanuel Ifeachor. "Video Compression." In Computer Communications and Networks, 53–72. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4905-7_3.

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Тези доповідей конференцій з теми "Video compression"

1

Xiaoran Hao, Bojin Zhuang, and Anni Cai. "Measurement compression in distributed compressive video sensing." In Multimedia Technology (IC-BNMT 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbnmt.2010.5705210.

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2

Asif, M. Salman, Felix Fernandes, and Justin Romberg. "Low-complexity video compression and compressive sensing." In 2013 Asilomar Conference on Signals, Systems and Computers. IEEE, 2013. http://dx.doi.org/10.1109/acssc.2013.6810345.

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3

Rippel, Oren, Sanjay Nair, Carissa Lew, Steve Branson, Alexander Anderson, and Lubomir Bourdev. "Learned Video Compression." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00355.

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4

Leguay, Thomas, Théo Ladune, Pierrick Philippe, and Olivier Déforges. "Cool-chic video: Learned video coding with 800 parameters." In 2024 Data Compression Conference (DCC). IEEE, 2024. http://dx.doi.org/10.1109/dcc58796.2024.00010.

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So, Simon W., and Clement H. C. Leung. "Inverted image indexing and compression." In Voice, Video, and Data Communications, edited by C. C. Jay Kuo, Shih-Fu Chang, and Venkat N. Gudivada. SPIE, 1997. http://dx.doi.org/10.1117/12.290346.

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6

Xiu, Xiaoyu, Yuwen He, Yan Ye, Rahul Vanam, Philippe Hanhart, Taoran Lu, Fangjun Pu, Peng Yin, Walt Husak, and Tao Chen. "Improved Video Coding Techniques for Next Generation Video Coding Standard." In 2019 Data Compression Conference (DCC). IEEE, 2019. http://dx.doi.org/10.1109/dcc.2019.00037.

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7

Chen, Cheng, Jingning Han, and Yaowu Xu. "Video Denoising for the Hierarchical Coding Structure in Video Coding." In 2020 Data Compression Conference (DCC). IEEE, 2020. http://dx.doi.org/10.1109/dcc47342.2020.00049.

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Barrett, Arjun, Laura Gomezjurado, Shuvam Mukherjee, Arz Bshara, Sahasrajit Sarmasarkar, Pulkit Tandon, and Tsachy Weissman. "Txt2Vid-Web: Web-based, Text-to-Video, Video Conferencing Pipeline." In 2023 Data Compression Conference (DCC). IEEE, 2023. http://dx.doi.org/10.1109/dcc55655.2023.00073.

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9

Szekiełda, Jakub, Adrian Dziembowski, and Dawid Mieloch. "The Influence of Coding Tools on Immersive Video Coding." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita, 2021. http://dx.doi.org/10.24132/csrn.2021.3002.21.

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Анотація:
This paper summarizes the research on the influence of HEVC(High Efficiency Video Coding)configuration on immersive video coding. The research was focused on the newest MPEG standard for immersive video compression –MIV (MPEG Immersive Video). The MIV standard is used as a preprocessing step before the typical video compression thus is agnostic to the video codec. Uncommon characteristics of videos produced by MIV causes, that the typical configuration of the video encoder (optimized for compression of natural sequences) is not optimal for such content. The experimental results prove, that the performance of video compression for immersive video can be significantly increased when selected coding tools are being used.
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Szekiełda, Jakub, Adrian Dziembowski, and Dawid Mieloch. "The Influence of Coding Tools on Immersive Video Coding." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita v Plzni, 2021. http://dx.doi.org/10.24132/csrn.2021.3101.21.

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Анотація:
This paper summarizes the research on the influence of HEVC (High Efficiency Video Coding) configuration on immersive video coding. The research was focused on the newest MPEG standard for immersive video compression – MIV (MPEG Immersive Video). The MIV standard is used as a preprocessing step before the typical video compression thus is agnostic to the video codec. Uncommon characteristics of videos produced by MIV causes, that the typical configuration of the video encoder (optimized for compression of natural sequences) is not optimal for such content. The experimental results prove, that the performance of video compression for immersive video can be significantly increased when selected coding tools are being used.
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Звіти організацій з теми "Video compression"

1

Zakhor, Avideh. Video Compression Algorithms for Transmission and Video. Fort Belvoir, VA: Defense Technical Information Center, May 1997. http://dx.doi.org/10.21236/ada327255.

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2

Venkatraman, Mahesh, Heesung Kwon, and Nasser M. Nasrabadi. Video Compression using Vector Quantization. Fort Belvoir, VA: Defense Technical Information Center, May 1998. http://dx.doi.org/10.21236/ada344253.

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3

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

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Woods, John W., and Shivkumar Kalyanaraman. Streaming Video Compression for Heterogeneous Networks. Fort Belvoir, VA: Defense Technical Information Center, April 2004. http://dx.doi.org/10.21236/ada424493.

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5

Fitzgerald, D. Market survey of video compression systems. Office of Scientific and Technical Information (OSTI), August 1989. http://dx.doi.org/10.2172/5342824.

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Ramchandran, Kannan. Unified Platform-Independent Airborne Networking Architecture for Video Compression. Fort Belvoir, VA: Defense Technical Information Center, July 2008. http://dx.doi.org/10.21236/ada484692.

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Fu, Chi Yung, and John E. Tope. Video Compression Routines Final Report CRADA No. TSB-1183-95. Office of Scientific and Technical Information (OSTI), February 2018. http://dx.doi.org/10.2172/1424652.

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Fu, C. Video Compression Routines Final Report CRADA No. TSB-1183-95. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/756386.

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Lin, Freddie. Edge Polynomial Fractal Compression Algorithm for High Quality Video Transmission. Final report. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/761345.

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Fu, Chi Yung ,. Petrich, L. I. ,. Lee, M. Image and video compression/decompression based on human visual perception system and transform coding. Office of Scientific and Technical Information (OSTI), February 1997. http://dx.doi.org/10.2172/489146.

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