Relevant bibliographies by topics / Lossless Compression Technique

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Academic literature on the topic 'Lossless Compression Technique'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Lossless Compression Technique"

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Kaur, Harjit. "Image Compression Techniques with LZW method." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1773–77. http://dx.doi.org/10.22214/ijraset.2022.39999.

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Abstract: Image compression is a technique which is used to reduce the size of the data. In other words, it means to remove the extra data from the available by applying some techniques and tricks which makes the data easy for storing and transmitting it over the transmission medium. The compression techniques are broadly divided into two categories. First one is Lossy Compression in which some of the data is lost while compressing it and second technique is lossless technique in which data is not lost after compressing it. These compression techniques can be applied on different image formats
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Salman, Ghalib Ahmed, Ahmed Ahmed, and HAREER MOAIAD HUSSEN. "Medical Image Compression Utilizing The Serial Differences and ‎Coding Techniques." InfoTech Spectrum: Iraqi Journal of Data Science 2, no. 1 (2025): 26–36. https://doi.org/10.51173/ijds.v2i1.13.

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Different medical devices for imaging used by centers and clinics produce an increasing number of sequential medical images. ‎Different imaging techniques such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Fluoroscopy ‎produce a set of series for the same patient. Within these images, most of the image parts are fixed against noticeable changes ‎in the remaining part. This consumes non-ignorable storage space. This paper proposes a near-lossless compression ‎technique that considers the fixed image parts to focus on changing parts for a higher compression ratio. In some app
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Emy, Setyaningsih, and Harjoko Agus. "Survey of Hybrid Image Compression Techniques." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2206–14. https://doi.org/10.11591/ijece.v7i4.pp2206-2214.

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A compression process is to reduce or compress the size of data while maintaining the quality of information contained therein. This paper presents a survey of research papers discussing improvement of various hybrid compression techniques during the last decade. A hybrid compression technique is a technique combining excellent properties of each group of methods as is performed in JPEG compression method. This technique combines lossy and lossless compression method to obtain a highquality compression ratio while maintaining the quality of the reconstructed image. Lossy compression technique
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Magar, Satyawati, and Bhavani Sridharan. "Comparative analysis of various Image compression techniques for Quasi Fractal lossless compression." International Journal of Computer Communication and Informatics 2, no. 2 (2020): 30–45. http://dx.doi.org/10.34256/ijcci2024.

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The most important Entity to be considered in Image Compression methods are Paek to signal noise ratio and Compression ratio. These two parameters are considered to judge the quality of any Image.and they a play vital role in any Image processing applications. Biomedical domain is one of the critical areas where more image datasets are involved for analysis and biomedical image compression is very, much essential. Basically, compression techniques are classified into lossless and lossy. As the name indicates, in the lossless technique the image is compressed without any loss of data. But in th
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Altamimi, Amal, and Belgacem Ben Youssef. "Lossless and Near-Lossless Compression Algorithms for Remotely Sensed Hyperspectral Images." Entropy 26, no. 4 (2024): 316. http://dx.doi.org/10.3390/e26040316.

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Rapid and continuous advancements in remote sensing technology have resulted in finer resolutions and higher acquisition rates of hyperspectral images (HSIs). These developments have triggered a need for new processing techniques brought about by the confined power and constrained hardware resources aboard satellites. This article proposes two novel lossless and near-lossless compression methods, employing our recent seed generation and quadrature-based square rooting algorithms, respectively. The main advantage of the former method lies in its acceptable complexity utilizing simple arithmetic
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P., Renukadevi. "Lossless Medical Image Compression by Multi Oriented Prediction Technique." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 1277–96. http://dx.doi.org/10.37200/ijpr/v24i5/pr201800.

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Ko, Yousun, Alex Chadwick, Daniel Bates, and Robert Mullins. "Lane Compression." ACM Transactions on Embedded Computing Systems 20, no. 2 (2021): 1–26. http://dx.doi.org/10.1145/3431815.

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This article presents Lane Compression, a lightweight lossless compression technique for machine learning that is based on a detailed study of the statistical properties of machine learning data. The proposed technique profiles machine learning data gathered ahead of run-time and partitions values bit-wise into different lanes with more distinctive statistical characteristics. Then the most appropriate compression technique is chosen for each lane out of a small number of low-cost compression techniques. Lane Compression’s compute and memory requirements are very low and yet it achieves a comp
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Patel, Jigar. "Enhanced Encoding Technique for Lossless Image Compression." RESEARCH HUB International Multidisciplinary Research Journal 9, no. 1 (2022): 01–09. http://dx.doi.org/10.53573/rhimrj.2022.v09i01.001.

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This paper proposes new encoding technique for lossless image compression. Here the pixel color information is stored in the file using efficient and sophisticated encoding technique which will be further compressed by existing compression algorithms and coding techniques. The final file with proposed extension generated by this scheme gives the better compression ratios than the existing image formats. The file is further decoded and image is recovered without any loss of information. The paper also discusses results and comparative analysis using popular image set compression ratio compariso
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Simanjuntak, Sari Magdalena. "Analisis Perbandingan Kompresi File Audio Menggunakan Algoritma Shannon Fano Dengan Algoritma Fibonacci Code." Jurnal Kajian Ilmiah Teknologi Informasi dan Komputer 2, no. 1 (2024): 1–10. http://dx.doi.org/10.62866/jutik.v2i1.110.

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Compression is a technique used to reduce the size of the data that serves to reduce memory capacity and speed up the data transfer process. In this study, the method used is the Shannon Fano method and the Fibonacci Code. In the Shannon Fano method the compression process is carried out by knowing the frequency of occurrence of each symbol which will then be sorted from the largest to the smallest frequency, while the Fibonacci Code method uses the Fibonacci integer series to encode the bit value of the data or file to be compressed. The file to be compressed is an audio file with an MP3 exte
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Setyaningsih, Emy, and Agus Harjoko. "Survey of Hybrid Image Compression Techniques." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2206. http://dx.doi.org/10.11591/ijece.v7i4.pp2206-2214.

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A compression process is to reduce or compress the size of data while maintaining the quality of information contained therein. This paper presents a survey of research papers discussing improvement of various hybrid compression techniques during the last decade. A hybrid compression technique is a technique combining excellent properties of each group of methods as is performed in JPEG compression method. This technique combines lossy and lossless compression method to obtain a high-quality compression ratio while maintaining the quality of the reconstructed image. Lossy compression technique
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Dissertations / Theses on the topic "Lossless Compression Technique"

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Blandon, Julio Cesar. "A novel lossless compression technique for text data." FIU Digital Commons, 1999. http://digitalcommons.fiu.edu/etd/1694.

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The focus of this thesis is placed on text data compression based on the fundamental coding scheme referred to as the American Standard Code for Information Interchange or ASCII. The research objective is the development of software algorithms that result in significant compression of text data. Past and current compression techniques have been thoroughly reviewed to ensure proper contrast between the compression results of the proposed technique with those of existing ones. The research problem is based on the need to achieve higher compression of text files in order to save valuable memory s
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Nicholl, Peter Nigel. "Feature directed spiral image compression : (a new technique for lossless image compression)." Thesis, University of Ulster, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339326.

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Neela, Divya. "Lossless medical image compression using integer transforms and predictive coding technique." Kansas State University, 2010. http://hdl.handle.net/2097/4615.

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Master of Science<br>Department of Electrical and Computer Engineering<br>D. V. Satish Chandra<br>The future of healthcare delivery systems and telemedical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing and communication techniques. E-health was born with the integration of networks and telecommunications when dealing with applications of collecting, sorting and transferring medical data from distant locations for performing remote medical collaborations and diagnosis. Healthcare systems in recent years rely on ima
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Bejile, Brian. "Bi-level lossless compression techniques." Diss., Connect to the thesis, 2004. http://hdl.handle.net/10066/1481.

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Contino, Sergio. "Development of Software Tools for the Test of Ultra Wide Band Receivers." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/4327/.

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In the last years, the importance of locating people and objects and communicating with them in real time has become a common occurrence in every day life. Nowadays, the state of the art of location systems for indoor environments has not a dominant technology as instead occurs in location systems for outdoor environments, where GPS is the dominant technology. In fact, each location technology for indoor environments presents a set of features that do not allow their use in the overall application scenarios, but due its characteristics, it can well coexist with other similar technologies, wi
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Ramírez, Jávega Francisco. "Graph-based techniques for compression and reconstruction of sparse sources." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/385349.

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The main goal of this thesis is to develop lossless compression schemes for analog and binary sources. All the considered compression schemes have as common feature that the encoder can be represented by a graph, so they can be studied employing tools from modern coding theory. In particular, this thesis is focused on two compression problems: the group testing and the noiseless compressed sensing problems. Although both problems may seem unrelated, in the thesis they are shown to be very close. Furthermore, group testing has the same mathematical formulation as non-linear binary source compr
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Liu, Yi. "Codage d'images avec et sans pertes à basse complexité et basé contenu." Thesis, Rennes, INSA, 2015. http://www.theses.fr/2015ISAR0028/document.

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Ce projet de recherche doctoral vise à proposer solution améliorée du codec de codage d’images LAR (Locally Adaptive Resolution), à la fois d’un point de vue performances de compression et complexité. Plusieurs standards de compression d’images ont été proposés par le passé et mis à profit dans de nombreuses applications multimédia, mais la recherche continue dans ce domaine afin d’offrir de plus grande qualité de codage et/ou de plus faibles complexité de traitements. JPEG fut standardisé il y a vingt ans, et il continue pourtant à être le format de compression le plus utilisé actuellement. B
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Tsai, Chang-Ta, and 蔡昌達. "A Study on Lossless Image Compression Based on the Pixel-value-difference Technique." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/07264876548233473447.

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碩士<br>國立臺北大學<br>資訊工程學系<br>103<br>In this thesis, a novel lossless image compression algorithm using pixel-value-difference technique is proposed. We observe that, in an image, values of two adjacent pixels are very close. Based on this observation, the distribution of difference values is a Laplacian-like distribution. Thus it can be compressed very well. Experiments show that the performance and the compression ratio of the proposed method are better than that of JPEG2000.
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Huang, Wen-Tsung, and 黃文聰. "Studies of Lossless Compression Algorithms for VQ Index and Their Application to Information Hiding Technique." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/78153790431472912341.

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碩士<br>大葉大學<br>資訊工程學系碩士班<br>93<br>As far as we know, for the compression of memoryless vector quantization (VQ), most of the lossless index coding algorithms are not suitable for various test images. As a result, we present a hybrid dynamic tree-coding (DTCS) and modified search order coding (MSOC) scheme called HLIC that re-encode the output index map efficiently without causing any extra coding distortion. The main idea behind this scheme is that the adjacent left and upper block around the current processed block usually provide more useful information than its adjacent left-upper and right-
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Hsiao, Ching-Wen, and 蕭景文. "Lossless and Lossy Compression Techniques for Corners and Contours." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/10082300319026280647.

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碩士<br>國立臺灣大學<br>電信工程學研究所<br>103<br>Shape is an important feature for object recognition, template matching, and image analysis. To represent it efficiently, the techniques for encoding the corners and the contours with very low bit rate are necessary. Therefore, in this thesis, three data compression techniques are proposed in order to reduce the data size requirement for corners and contours. For corner compression, we rearrange the corners based on the distance information and use an active matrix to encode the position of corners. Moreover, the techniques of adaptive arithmetic coding a
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Books on the topic "Lossless Compression Technique"

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Nicholl, Peter Nigel. Feature directed spiral image compression (a new technique for lossless image compression). The Author], 1994.

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Mielikaïnen, Jarno. Lossless compression of hyperspectral images. Lappeenranta University of Technology, 2003.

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El-Ghoboushi, Mohammad. Comparison of Lossless Image Compression Techniques Based on Context Modeling. GRIN Verlag GmbH, 2015.

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Book chapters on the topic "Lossless Compression Technique"

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Moses, Diana, and C. Deisy. "A Novel Lossless ECG Compression Technique for Transmission in GSM Networks." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1768-8_78.

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Van Assche, Steven, Wilfried Philips, and Ignace Lemahieu. "Lossless compression of pre-press images using a novel colour decorrelation technique." In Image Analysis and Processing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63508-4_109.

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Al-Nassrawy, Kahlaa K., Ali Kadhum Idrees, and Dhiah Al-Shammary. "A Novel Lossless EEG Compression Model Using Fractal Combined with Fixed-Length Encoding Technique." In AI and IoT for Sustainable Development in Emerging Countries. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90618-4_21.

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Mainalli, Sanjay, and Kalpana Sharma. "An Efficient Technique for Lossless Address Data Compression Using Novel Adaptive SPIHT Algorithm in WSN." In International Conference on Mobile Computing and Sustainable Informatics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49795-8_8.

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Yamagiwa, Shinichi. "Stream-Based Lossless Data Compression." In Sublinear Computation Paradigm. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4095-7_16.

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AbstractIn this chapter, we introduce aspects of applying data-compression techniques. First, we study the background of recent communication data paths. The focus of this chapter is a fast lossless data-compression mechanism that handles data streams completely. A data stream comprises continuous data with no termination of the massive data generated by sources such as movies and sensors. In this chapter, we introduce LCA-SLT and LCA-DLT, which accept the data streams, as well as several implementations of these stream-based compression techniques. We also show optimization techniques for opt
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Ševčík, Jiří, and Jiří Dvorský. "Techniques of Czech Language Lossless Text Compression." In Computer Information Systems and Industrial Management. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45378-1_24.

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Hossain, Mohammad Badrul, and Md Nowroz Junaed Rahman. "An Empirical Analysis on Lossless Compression Techniques." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35299-7_13.

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Djebbar, Fatiha, and Beghdad Ayad. "Audio Steganalysis Based on Lossless Data-Compression Techniques." In Information and Communications Security. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34129-8_1.

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Chun, Youngjae, Sunyong Park, and Kyoungsu Oh. "Multiple Layer Displacement Mapping with Lossless Image Compression." In Entertainment for Education. Digital Techniques and Systems. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14533-9_53.

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Kumar, Vivek, Gursharan Singh, and Iqbal Singh. "A Review on Geo-location-Based Authentication with Various Lossless Compression Techniques." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7346-8_31.

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Conference papers on the topic "Lossless Compression Technique"

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Yi, Shiyan, Xinlin Wei, Libo Lin, Peng Zhang, and Yibo Fan. "An Efficient Lossless Gradient Compression Technique for Distributed Training Systems." In 2025 Data Compression Conference (DCC). IEEE, 2025. https://doi.org/10.1109/dcc62719.2025.00100.

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Liu, Bryan, Alvaro Valcarce, and K. Pavan Srinath. "A Lossless Compression Technique for the Downlink Control Information Message." In 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2024. http://dx.doi.org/10.1109/spawc60668.2024.10694087.

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Ishak, Izlin Zuriani, Liew Seow Wooi, Nur Ziadah Harun, Nur Shahirah Azahari, Sofia Najwa Ramli, and Osman Ghazali. "A Comparative Study of Lossless Compression Technique in Quantum Secure Direct Communication." In 2024 1st International Conference on Cyber Security and Computing (CyberComp). IEEE, 2024. https://doi.org/10.1109/cybercomp60759.2024.10913632.

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Challapalli, Kausik, Vivek Kothamasu, Hasha Garikapati, Roop Sai Charan, ManiSankar Thota, and Satish Anamalamudi. "Analysing Lossless Image Compression Techniques for IoT Devices." In 2024 Third International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2024. http://dx.doi.org/10.1109/iceeict61591.2024.10718516.

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Gupta, Krishan, Mukesh Sharma, and Pallavi Sharma. "Lossless compression based Kmp technique." In 2014 International Conference on Optimization, Reliabilty, and Information Technology (ICROIT). IEEE, 2014. http://dx.doi.org/10.1109/icroit.2014.6798363.

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Rahman, Md Atiqur, Most Jannatul Ferdous, Md Mamun Hossain, Md Rashedul Islam, and Mohamed Hamada. "A lossless speech signal compression technique." In 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT). IEEE, 2019. http://dx.doi.org/10.1109/icasert.2019.8934484.

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Gupta, Krishan, Mukesh Sharma, and Kirti Saneja. "A new lossless KMK technique for image compression." In 2014 International Conference on Optimization, Reliabilty, and Information Technology (ICROIT). IEEE, 2014. http://dx.doi.org/10.1109/icroit.2014.6798364.

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Rahman, Md Atiqur, Jungpil Shin, Aloke Kumar Saha, and Md Rashedul Islam. "A Novel Lossless Coding Technique for Image Compression." In 2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR). IEEE, 2018. http://dx.doi.org/10.1109/iciev.2018.8641065.

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Xu zhili and Wang hongxia. "Lossless data compression technique for spatial data system." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5619021.

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Allred, Lloyd G., and Gary E. Kelly. "Lossless image compression technique for infrared thermal images." In Aerospace Sensing, edited by David P. Casasent and Andrew G. Tescher. SPIE, 1992. http://dx.doi.org/10.1117/12.60564.

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