Relevant bibliographies by topics / Lempel-Ziv decompression

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Academic literature on the topic 'Lempel-Ziv decompression'

Author: Grafiati
Published: 11 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Lempel-Ziv decompression"

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Maharjan, Shyam, Sujan Poudel, and Dipesh Tandukar. "A Comparative Study of Text-Based Lossless Compression." American Journal of Smart Technology and Solutions 3, no. 2 (2024): 34–39. http://dx.doi.org/10.54536/ajsts.v3i2.3566.

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Lossless data compression is a critical technique used to reduce file sizes without any loss of information during the encoding and decoding processes. This study presents a comparative analysis of two widely-used lossless compression algorithms: Huffman Encoding and Lempel-Ziv-Welch (LZW). The primary objective is to evaluate the performance of these algorithms in terms of compression ratio, compression time, decompression time, and space savings. The analysis was conducted on 100 files of varying sizes. The results demonstrate that the LZW algorithm outperforms Huffman Encoding, offering sup
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Shirakol, Shrikanth, Akshata Koparde, Sandhya ., Shravan Kulkarni, and Yogesh Kini. "Performance optimization of dual stage algorithm for lossless data compression and decompression." International Journal of Engineering & Technology 7, no. 2.21 (2018): 127. http://dx.doi.org/10.14419/ijet.v7i2.21.11849.

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In this paper, an optimized dual stage architecture is proposed which is the combination of Lempel-Ziv-Welch (LZW) Algorithm at the first phase and Arithmetic Coding being the later part of Architecture. LZW Algorithm is a lossless compression algorithm and code here for each character is available in the dictionary which reduces 5-bits per cycle as compared to ASCII. In arithmetic coding the numbers are represented by an interval of real numbers from zero to one according to their probabilities. It is an entropy coding and is lossless in nature. The text information is allowed to pass through
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Keerthy, A. S., and Manju Priya S. "Genomic Sequence Data Compression using Lempel-Ziv-Welch Algorithm with Indexed Multiple Dictionary." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 2 (2019): 541–47. https://doi.org/10.35940/ijeat.B3278.129219.

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With the advancement in technology and development of High Throughput System (HTS), the amount of genomic data generated per day per laboratory across the globe is surpassing the Moore’s law. The huge amount of data generated is of concern to the biologists with respect to their storage as well as transmission across different locations for further analysis. Compression of the genomic data is the wise option to overcome the problems arising from the data deluge. This paper discusses various algorithms that exists for compression of genomic data as well as a few general purpose algorithms
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King, G. R. Gnana, C. Christopher Seldev, and N. Albert Singh. "A Novel Compression Technique for Compound Images Using Parallel Lempel-Ziv-Welch Algorithm." Applied Mechanics and Materials 626 (August 2014): 44–51. http://dx.doi.org/10.4028/www.scientific.net/amm.626.44.

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Compound image is a combination of natural images, text, and graphics.This paper presents a compression technique for improving coding efficiency. The algorithm first decomposes the compound images by using 3 level biorthogonal wavelet transform and then the transformed image was further compressed by Parallel dictionary based LZW algorithm called PDLZW.In PDLZW algorithm instead of using a unique fixed word width dictionary a hierarchical variable word width dictionary set containing several dictionaries of small address space and increases the word widths used for compression and decompressi
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Fitra Wijayanto, Erick, Muhammad Zarlis, and Zakarias Situmorang. "Increase the PSNR Of Image Using LZW and AES Algorithm With MLSB on Steganography." International Journal of Engineering & Technology 7, no. 2.5 (2018): 119. http://dx.doi.org/10.14419/ijet.v7i2.5.13965.

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There are many research has done a hybridization approach of text message insertion that has been compressed with Lempel-Ziv-Welch (LZW) algorithm and has also been encrypted. The text messages in ciphertext form are inserted into the image file using LSB (Least Significant Bit) method. The results of this study indicate that the value of Peak Signal to Noise Ratio (PSNR) lower than the LSB method of 0.94 times with a ratio of 20.33%, with Kekre's method of 10.04%. To improve the value of PSNR stego image of insertion, in this research is inserted audio samples using 5 bits to reduce the amoun
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Anandita, Ida Bagus Gede, I. Gede Aris Gunadi, and Gede Indrawan. "Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding." SINTECH (Science and Information Technology) Journal 1, no. 1 (2018): 7–15. http://dx.doi.org/10.31598/sintechjournal.v1i1.179.

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Technological progress in the medical area made medical images like X-rays stored in digital files. The medical image file is relatively large so that the image needs to be compressed. The lossless compression technique is an image compression where the decompression results are the same as the original or no information lost in the compression process. The existing algorithms on lossless compression techniques are Run Length Encoding (RLE), Huffman, and Lempel Ziv Welch (LZW). This study compared the performance of the three algorithms in compressing medical images. The result of image decomp
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Huang, Xiaobo, and Limin Yan. "P‐5.24: A Lossless Image Compression LZW Algorithm Based on Double Hash Dictionary." SID Symposium Digest of Technical Papers 56, S1 (2025): 1119–24. https://doi.org/10.1002/sdtp.19013.

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Among numerous lossless image compression algorithms, the LZW (Lempel‐Ziv‐Welch) algorithm is widely used due to its high adaptability and coding efficiency. However, the LZW algorithm has certain limitations as it is susceptible to factors such as dictionary storage structure and dictionary update strategies, often failing to balance compression ratio and speed. Therefore, this paper proposes an improved LZW algorithm based on a double‐hash dictionary. The update strategy involves using both an improved dictionary and the original dictionary, where frequently occurring strings in the original
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Nunes, Daniel S. N., Felipe A. Louza, Simon Gog, Mauricio Ayala-Rincón, and Gonzalo Navarro. "Grammar Compression by Induced Suffix Sorting." ACM Journal of Experimental Algorithmics 27 (December 31, 2022): 1–33. http://dx.doi.org/10.1145/3549992.

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A grammar compression algorithm, called GCIS, is introduced in this work. GCIS is based on the induced suffix sorting algorithm SAIS, presented by Nong et al. in 2009. The proposed solution builds on the factorization performed by SAIS during suffix sorting. A context-free grammar is used to replace factors by non-terminals. The algorithm is then recursively applied on the shorter sequence of non-terminals. The resulting grammar is encoded by exploiting some redundancies, such as common prefixes between right-hands of rules, sorted according to SAIS. GCIS excels for its low space and time requ
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Belu, Sabin, and Daniela Coltuc. "A Hybrid Data-Differencing and Compression Algorithm for the Automotive Industry." Entropy 24, no. 5 (2022): 574. http://dx.doi.org/10.3390/e24050574.

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We propose an innovative delta-differencing algorithm that combines software-updating methods with LZ77 data compression. This software-updating method relates to server-side software that creates binary delta files and to client-side software that performs software-update installations. The proposed algorithm creates binary-differencing streams already compressed from an initial phase. We present a software-updating method suitable for OTA software updates and the method’s basic strategies to achieve a better performance in terms of speed, compression ratio or a combination of both. A compari
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Kadhim, Doaa J., Mahmood F. Mosleh, and Faeza A. Abed. "Exploring Text Data Compression: A Comparative Study of Adaptive Huffman and LZW Approaches." BIO Web of Conferences 97 (2024): 00035. http://dx.doi.org/10.1051/bioconf/20249700035.

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Data compression is a critical procedure in computer science that aims to minimize the size of data files while maintaining their vital information. It is extensively utilized in Numerous applications, including communication, data storage, and multimedia transmission. In this work, we investigated the results of compressing four different text files with Lempel-Ziv-Welch compression techniques and Adaptive Huffman coding. The experiment used four text files: Arabic and English paragraphs and repeated Arabic and English characters. We measured Bit-rate, Compression Time, and Decompression Time
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Dissertations / Theses on the topic "Lempel-Ziv decompression"

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Rossi, Massimiliano. "Algorithms and Data Structures for Coding, Indexing, and Mining of Sequential Data." Doctoral thesis, 2020. http://hdl.handle.net/11562/1010405.

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In recent years, the production of sequential data has been rapidly increasing. This requires solving challenging problems about how to represent information, how to retrieve information, and how to extract knowledge, from sequential data. These questions belong to the areas of coding, indexing, and mining, respectively. In this thesis, we investigate problems from those three areas. Coding refers to the way in which information is represented. Coding aims at generating optimal codes, that are codes having a minimum expected length. Codes can be generated for different purposes, from data co
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Conference papers on the topic "Lempel-Ziv decompression"

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Puglisi, Simon J., and Massimiliano Rossi. "On Lempel-Ziv Decompression in Small Space." In 2019 Data Compression Conference (DCC). IEEE, 2019. http://dx.doi.org/10.1109/dcc.2019.00030.

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Conrad, Kennon J., and Paul R. Wilson. "Grammatical Ziv-Lempel Compression: Achieving PPM-Class Text Compression Ratios with LZ-Class Decompression Speed." In 2016 Data Compression Conference (DCC). IEEE, 2016. http://dx.doi.org/10.1109/dcc.2016.119.

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Bille, Philip, Mikko Berggren Ettienne, Travis Gagie, Inge Li Gortz, and Nicola Prezza. "Decompressing Lempel-Ziv Compressed Text." In 2020 Data Compression Conference (DCC). IEEE, 2020. http://dx.doi.org/10.1109/dcc47342.2020.00022.

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