Relevant bibliographies by topics / Video compression algorithms

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Video compression algorithms'

Author: Grafiati
Published: 5 June 2025
Last updated: 25 June 2025

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Journal articles on the topic "Video compression algorithms"

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

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

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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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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 (2016): 6671–79. http://dx.doi.org/10.1166/jctn.2016.5613.

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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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Fitrya, Soraya Ainun. "Perbandingan Algoritma Elias Omega Code Dan Elias Delta Code Dalam Mengkompresi File Video (Mp4)." Bulletin of Information System Research 1, no. 3 (2023): 110–19. https://doi.org/10.62866/bios.v1i3.29.

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The video file size is quite large where the better the video file quality and the longer the video file time, the file size is quite large in storing the file. With the video file size which greatly affects the length of time the video file is sent. The solution to this problem is to compress the video file. There are many algorithms in video file compression, for example the elias omega code algorithm, elias delta code, stout code, punctured elias code and many other compression algorithms. So with so many algorithms, it is necessary to test several compression algorithms or algorithm comparisons. Algorithm comparison aims to find out which algorithm is more accurate in carrying out the data compression process. The algorithms that will be compared are elias omega code and elias delta code. While the comparison parameters of the two algorithms are the compression ratio and space saving.
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Kadhim, Amal Abbas, Azal Minshed Abid, and Zuhair Hussein Ali. "Subject Review: Video Compression Algorithms." International Journal of Engineering Research and Advanced Technology 06, no. 11 (2020): 21–25. http://dx.doi.org/10.31695/ijerat.2020.3668.

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Zhu, Ye. "An investigation of machine learning-based video compression techniques." Applied and Computational Engineering 47, no. 1 (2024): 23–27. http://dx.doi.org/10.54254/2755-2721/47/20241113.

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As video technology continues to seamlessly weave itself into the fabric of daily life, there is a growing need for enhanced storage and efficient video transmission. This surge in demand has led to heightened expectations and standards for video compression technology. Machine learning as an up-and-coming technology can play its advantages in the field of video compression. This article reviews the current state of research on combining video compression techniques with machine learning. The article provides an overview of various research avenues for enhancement, spanning from conventional video compression algorithms to the fusion of traditional compression frameworks with machine learning methodologies, and even the development of novel end-to-end compression algorithms. In additional, the article explores the possible various application scenarios of machine learning-based video compression algorithms based on the characteristics of such non-standard and arithmetic demanding algorithms. At the end, the article speculates on the future of video compression algorithms based on the content of the various studies reviewed in the article.
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Mochurad, Lesia. "A Comparison of Machine Learning-Based and Conventional Technologies for Video Compression." Technologies 12, no. 4 (2024): 52. http://dx.doi.org/10.3390/technologies12040052.

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The growing demand for high-quality video transmission over bandwidth-constrained networks and the increasing availability of video content have led to the need for efficient storage and distribution of large video files. To improve the latter, this article offers a comparison of six video compression methods without loss of quality. Particularly, H.255, VP9, AV1, convolutional neural network (CNN), recurrent neural network (RNN), and deep autoencoder (DAE). The proposed decision is to use a dataset of high-quality videos to implement and compare the performance of classical compression algorithms and algorithms based on machine learning. Evaluations of the compression efficiency and the quality of the received images were made on the basis of two metrics: PSNR and SSIM. This comparison revealed the strengths and weaknesses of each approach and provided insights into how machine learning algorithms can be optimized in future research. In general, it contributed to the development of more efficient and effective video compression algorithms that can be useful for a wide range of applications.
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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 (2021): 1256–72. http://dx.doi.org/10.17762/turcomat.v12i5.1793.

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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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Pandit, Shraddha, Piyush Kumar Shukla, Akhilesh Tiwari, Prashant Kumar Shukla, Manish Maheshwari, and Rachana Dubey. "Review of video compression techniques based on fractal transform function and swarm intelligence." International Journal of Modern Physics B 34, no. 08 (2020): 2050061. http://dx.doi.org/10.1142/s0217979220500617.

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Data processing with multiple domains is an important concept in any platform; it deals with multimedia and textual information. Where textual data processing focuses on a structured or unstructured way of data processing which computes in less time with no compression over the data, multimedia data are processing deals with a processing requirement algorithm where compression is needed. This involve processing of video and their frames and compression in short forms such that the fast processing of storage as well as the access can be performed. There are different ways of performing compression, such as fractal compression, wavelet transform, compressive sensing, contractive transformation and other ways. One way of performing such a compression is working with the high frequency component of multimedia data. One of the most recent topics is fractal transformation which follows the block symmetry and archives high compression ratio. Yet, there are limitations such as working with speed and its cost while performing proper encoding and decoding using fractal compression. Swarm optimization and other related algorithms make it usable along with fractal compression function. In this paper, we review multiple algorithms in the field of fractal-based video compression and swarm intelligence for problems of optimization.
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Prajapati, Y. N., and M. K. Srivastava. "Novel algorithms for protective digital privacy." IAES International Journal of Robotics and Automation (IJRA) 8, no. 3 (2019): 184–88. https://doi.org/10.11591/ijra.v8i3.pp184-188.

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Video is the recording, reproducing, or broadcasting of moving visual images. Visual multimedia source that combines a sequence of images to form a moving picture. The video transmits a signal to a screen and processes the order in which the screen captures should be shown. Videos usually have audio components that correspond with the pictures being shown on the screen. Video compression technologies are about reducing and removing redundant video data so that a digital video file can be effectively sent over a network and stored on computer disks. With efficient compression techniques, a significant reduction in file size can be achieved with little or no adverse effect on the visual quality. The video quality, however, can be affected if the file size is further lowered by raising the compression level for a given compression technique. Security is about the protection of assets. Security, in information technology (IT), is the defense of digital information and IT assets against internal and external, malicious and accidental threats. This defense includes detection, prevention and response to threats through the use of security policies, software tools and IT services. Security refers to protective digital privacy measures that are applied to prevent unauthorized access to computers, databases and websites. Cryptography is closely related to the disciplines of cryptology and cryptanalysis. Cryptography includes techniques such as microdots, merging words with images, and other ways to hide information in storage or transit. However, in today's computer-centric world, cryptography is most often associated with scrambling plaintext (ordinary text, sometimes referred to as clear text into cipher text (a process called encryption), then back again (known as decryption). Cryptography is evergreen and developments. Cryptography protects users by providing functionality for the encryption of data and authentication of other users. Compression is the process of reducing the number of bits or bytes needed to represent a given set of data. It allows saving more data. The project aims to implement security algorithm for data security. The data will be first encrypted using security techniques and that are done at the same time then it takes less processing time and more speed compression techniques will applied. If encryption and compression are done at the same time then it takes less processing time and more speed.
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Dissertations / Theses on the topic "Video compression algorithms"

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Thom, Gary A., and Alan R. Deutermann. "A COMPARISON OF VIDEO COMPRESSION ALGORITHMS." International Foundation for Telemetering, 2000. http://hdl.handle.net/10150/608290.

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International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California<br>Compressed video is necessary for a variety of telemetry requirements. A large number of competing video compression algorithms exist. This paper compares the ability of these algorithms to meet criteria which are of interest for telemetry applications. Included are: quality, compression, noise susceptibility, motion performance and latency. The algorithms are divided into those which employ inter-frame compression and those which employ intra-frame compression. A video tape presentation will also be presented to illustrate the performance of the video compression algorithms.
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Gao, Wenfeng. "Real-time video postprocessing algorithms and metrics /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5913.

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Stewart, Graeme Robert. "Implementing video compression algorithms on reconfigurable devices." Thesis, University of Glasgow, 2010. http://theses.gla.ac.uk/1267/.

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The increasing density offered by Field Programmable Gate Arrays(FPGA), coupled with their short design cycle, has made them a popular choice for implementing a wide range of algorithms and complete systems. In this thesis the implementation of video compression algorithms on FPGAs is studied. Two areas are specifically focused on; the integration of a video encoder into a complete system and the power consumption of FPGA based video encoders. Two FPGA based video compression systems are described, one which targets surveillance applications and one which targets video conferencing applications. The FPGA video surveillance system makes use of a novel memory format to improve the efficiency with which input video sequences can be loaded over the system bus. The power consumption of a FPGA video encoder is analyzed. The results indicating that the motion estimation encoder stage requires the most power consumption. An algorithm, which reuses the intra prediction results generated during the encoding process, is then proposed to reduce the power consumed on an FPGA video encoder’s external memory bus. Finally, the power reduction algorithm is implemented within an FPGA video encoder. Results are given showing that, in addition to reducing power on the external memory bus, the algorithm also reduces power in the motion estimation stage of a FPGA based video encoder.
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GONZALES, JOSE ANTONIO CASTINEIRA. "EVALUATING MOTION ESTIMATION ALGORITHMS FOR VIDEO COMPRESSION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1996. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8711@1.

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Este trabalho teve por objetivo estudar algoritmos de estimação de movimento baseados na técnica de casamento de bloco a fim de avaliar a importância da sua escolha na construção de um codificador para uso em compressão de seqüência de imagens. Para isto foram estudados quatro algoritmos baseados na técnica de casamento de bloco, sendo verificada a interdependência existente entre os vários parâmetros que os compõem, tais como, tamanho da área de busca, critérios de medida de distorção entre blocos e tamanhos de blocos, em relação à qualidade da imagem reconstruída.<br>This work was performed to study motion estimation algorithms based on block matching in order to evaluate the importance of the choice of the motion estimation algorithm in the Project of a image sequence compression coder. In order to do so, they were studied four motion estimation algorithms, and their performance were evaluated considering some parameters such as search region size, methods to measure the matching between blocks and block sizes, related to the quality of the reconstructed image.
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Tsoligkas, Nick A. "Video/Image Processing Algorithms for Video Compression and Image Stabilization Applications." Thesis, Teesside University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517469.

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As the use of video becomes increasingly popular and wide spread in the areas of broadcast services, internet, entertainment and security-related applications, providing means for fast. automated, and effective techniques to represent video based on its content, such as objects and meanings, is important topic of research. In many applications.. removing the hand shaking effect and making video images stable and clear or decomposing (and then transmitting) the video content into a collection of meaningful objects is a necessity. Therefore automatic techniques for video stabilization, extraction of objects from video data as well as transmitting their shapes, motion and texture at very low bit rates over error networks, are desired. In this thesis the design of a new low bit rate codec is presented. Furthermore a method about video stabilization is introduced. The main technical contributions resulted from this work are as follows. Firstly, an adaptive change detection algorithm identifies the objects from the background. The luminance difference between framer~ in the first stage, is modelled so as to separate contributions caused by noise and illumination variations from those caused by meaningful moving objects. In the second stage the segmentation tool based on image blocks, histograms and clustering algorithms segments the difference image into areas corresponding to objects. In the third stage morphological edge detection, contour analysis, and object labelling are the main tasks of the proposed segmentation algorithm. Secondly, a new low bit rate codec is designed and analyzed based on the proposed segmentation tool. The estimated motion vectors inside the change detection mask, the comer points of the shapes as well as the residual information inside the motion failure regions are transmitted to the decoder using different coding techniques, thus achieving efficient compression. Thirdly, a novel approach of estimating and removing unwanted video motion, which does not require accelerators or gyros, is presented. The algorithm estimates the camera motion from the incoming video stream and compensates for unwanted translation and rotation. A synchronization unit supervises and generates the stabilized video sequence. The reliability of all the proposed algorithms is demonstrated by extensive experimentation on various video shots.
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Lee, Woobin. "Architectures and algorithms for MPEG video coding /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/5888.

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Ng, Cheuk-yan, and 吳卓恩. "Rate control algorithms for video coding." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B29729361.

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Ng, Cheuk-yan. "Rate control algorithms for video coding /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25151289.

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Lewis, A. S. "Image and video compression using the wavelet transform." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318148.

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Chen, Xiaolin. "Algorithms and Architectures for Lossless Image and Video Compression." Thesis, University of Bristol, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520252.

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Books on the topic "Video compression algorithms"

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2.

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Furht, Borivoje. Motion estimation algorithms for video compression. Kluwer Academic Publishers, 1997.

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Furht, Borko. Motion estimation algorithms for video compression. Kluwer, 1997.

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Furht, Borivoje. Motion Estimation Algorithms for Video Compression. Springer US, 1997.

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1955-, Vitter Jeffrey Scott, ed. Efficient algorithms for MPEG video compression. Wiley, 2002.

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

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

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Westwater, Raymond. Real-time video compression: Techniques and algorithms. Kluwer, 1997.

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Bhaskaran, Vasudev. Image and video compression standards: Algorithms and architectures. Kluwer Academic Publishers, 1995.

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Huifang, Sun, ed. Image and video compression for multimedia engineering: Fundamentals, algorithms, and standards. 2nd ed. CRC Press, 2008.

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Book chapters on the topic "Video compression algorithms"

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "Video Compression Techniques." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_2.

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Furht, Borko, Stephen W. Smoliar, and HongJiang Zhang. "Implementations of Compression Algorithms." In Video and Image Processing in Multimedia Systems. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2277-5_9.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "The Problem of Video Compression." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_1.

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Rosário Lucas, Luís Filipe, Eduardo Antônio Barros da Silva, Sérgio Manuel Maciel de Faria, Nuno Miguel Morais Rodrigues, and Carla Liberal Pagliari. "Image and Video Coding Standards." In Efficient Predictive Algorithms for Image Compression. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51180-1_3.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "Fast Search Algorithms: New Results." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_6.

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Hadar, Ofer, and Raz Birman. "Deep Learning in Video Compression Algorithms." In Multi-faceted Deep Learning. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-030-74478-6_8.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "Motion Compensation and Estimation." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_3.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "Experiments on Current Motion Estimation Techniques." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_4.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "The Motion Compensation Hypothesis." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_5.

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Furht, Borko, Joshua Greenberg, and Raymond Westwater. "Conclusions and Research Directions." In Motion Estimation Algorithms for Video Compression. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2_7.

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Conference papers on the topic "Video compression algorithms"

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Guzmán, Felipe, and Esteban Vera. "Coded aperture strategies for high-speed video sensing." In Computational Optical Sensing and Imaging. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cosi.2024.cth4a.1.

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This work discusses innovative high-speed imaging methods, merging hard-ware and algorithms in computational imaging. It focuses on techniques like rolling shutter, and coded aperture compressive temporal imaging for efficient data capture and high-quality compression.
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Kondo, Yuichi, and Yuichi Kusakabe. "Adaptive Bit Allocation Algorithm in Two-Pass Video Coding." In 2025 Data Compression Conference (DCC). IEEE, 2025. https://doi.org/10.1109/dcc62719.2025.00069.

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Xing, Feng, Yingwen Zhang, Meng Wang, et al. "An Efficient Hidden Markov Model-Based Sample Adaptive Offset Mode Decision Algorithm for Versatile Video Coding." In 2025 Data Compression Conference (DCC). IEEE, 2025. https://doi.org/10.1109/dcc62719.2025.00094.

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Cheung, Ngai-Man, and Antonio Ortega. "Compression algorithms for flexible video decoding." In Electronic Imaging 2008, edited by William A. Pearlman, John W. Woods, and Ligang Lu. SPIE, 2008. http://dx.doi.org/10.1117/12.770397.

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Rahman, Tarif Riyad, and Miftahur Rahman. "Compression Algorithms for Audio-Video Streaming." In 2010 International Conference on Intelligent Systems, Modelling and Simulation (ISMS). IEEE, 2010. http://dx.doi.org/10.1109/isms.2010.44.

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Galteri, Leonardo, Marco Bertini, Lorenzo Seidenari, and Alberto Del Bimbo. "Video Compression for Object Detection Algorithms." In 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018. http://dx.doi.org/10.1109/icpr.2018.8546064.

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Mozammil, S. M. Zakariya, and M. Inamullah. "Analysis of Video Compression Algorithms on Different Video Files." In 2012 4th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2012. http://dx.doi.org/10.1109/cicn.2012.49.

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Yi-Jen Chin and T. Berger. "Perceptual rate control algorithms for fax-based video compression." In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582086.

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Ratakonda, Krishna, and Ligang Lu. "Incorporating content sensitivity into standard video compression algorithms." In Information Technologies 2000, edited by Andrew G. Tescher, Bhaskaran Vasudev, and V. Michael Bove, Jr. SPIE, 2001. http://dx.doi.org/10.1117/12.420833.

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Caputo, Carlo "zED." "Optimization of video compression parameters through genetic algorithms." In Companion the XIV Brazilian Symposium. ACM Press, 2008. http://dx.doi.org/10.1145/1809980.1809990.

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Reports on the topic "Video compression algorithms"

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

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Smith, Michael, Jonathan Bisila, Renee Gooding, and Christina Ting. Identifying and Explaining Anomalous Activity in Surveillance Video with Compression Algorithms. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2430331.

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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), 1999. http://dx.doi.org/10.2172/761345.

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Li, Baisong, and Bo Xu. PR-469-19604-Z01 Auto Diagnostic Method Development for Ultrasonic Flow Meter. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012204.

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Abstract:
The objectives of this research are to develop methods for performing ultrasonic flow meter (USM) diagnostic evaluation automatically and a software tool with all necessary attachments. USM-based diagnostics have been established and thirteen categories of knowledge rules of existing cases have been learned and integrated. A search engine for relevant standards, specifications, and other documents of the measurement system has been developed, which enables the free search of text content. Further, with the assistance of modern reasoning techniques, the authorized user only needs to configure an EXCEL file or scripts to activate the rules of the knowledge base by using Drools technology. Therefore, the integration of any potential knowledge rules is convenient and requires no professional skills or changing of the internal source code of the software. Secondly, a new flow meter diagnostic method is proposed based on multiple information methodologies and it is based on the real-time measurement data, operation data, and video data if applicable. The method is intended to identify abnormal states of the measurement system on a real-time basis with the assistance of the knowledge rules and to provide a strategy for mitigating the meter error of components within the measurement system. Thirdly, the applications of Gaussian quadrature diagnostics in daily acquisition nomination change situations and compressor-induced pulsating flow scenarios have been investigated and results are shown in the document. Based on the results, it can be concluded that the measurement uncertainty caused by compressor-induced pulsating flows is obvious, while the measurement uncertainty caused by daily acquisition nomination change is relatively smaller. The software is then developed based on the knowledge, the idea of multiple information methods, and applications of the Gaussian quadrature diagnostics method with all necessary attachments. The architecture, the algorithm, and a few examples are introduced.
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