Introduction to Data Compression

By Tinku Acharya, Ping-Sing Tsai. 2005

1,647 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/7ee9bfcf8a3c8110cc8cf1779f2dc5d4ce3e316e

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In Computational Theory and Mathematics

Citations in the corpus

Photographic Image Synthesis with Cascaded Refinement Networks (2017, background): “The best existing image compression techniques require millions of bits of information to represent the content of a single high-resolution image: there exists no known way to reconstruct a given photograph at high fidelity from a lowercapacity representation [40].”
Constant Composition Distribution Matching (2015, background): “A more detailed explanation of scaling for arithmetic coding can be found for instance in [19, Chap.”
Encyclopedia of Healthcare Information Systems (2008, background): “Signal compression has been widely studied during the past decades, and several references discuss this subject (Gersho & Gray, 1992; Jayant & Noll, 1982; Sayood, 1996).”
Formalizing Human Ingenuity: A Quantitative Framework for Copyright Law's Substantial Similarity (2022, methodology): “Table 4: Our framework’s treatment of Computer Associates v. Altai store their own dictionaries in this way [80, ch. 5]; in contrast our naive dictionary approach insists upon using the log of the number of entries in the dictionary to index within it.”
An Energy-Efficient Data Collection Framework for Wireless Sensor Networks by Exploiting Spatiotemporal Correlation (2007, positive): “The difference distortion measure has been broadly used in image compression to evaluate the fidelity of a reconstructed image against the original image [23].”
An Information-theoretic Framework for Visualization (2010, background): “We thereby compiled a collection of major information theoretic concepts and applications based on a number of textbooks, including [1, 11, 19, 22, 35, 44, 47].”
Silent Data Corruptions at Scale (2021, background): “Interested readers can review the following papers for details and comparison of compression algorithms [30], [12], [25].”
Inattentive Valuation and Reference-Dependent Choice ∗ (2012, methodology): “The study of optimal information structures in this sense also corresponds to a familiar problem in the computer science literature, namely the analysis of “optimal quantization” in coding theory (Sayood, 2005).”
Task-Oriented Multi-User Semantic Communications (2021, methodology): “…e.g., millimeter wave/terahertz communications [2], [3], massive antennas array [4], and reconﬁgurable intelligent surfaces [5]; 2) improvement of software to optimize the utilization of communication resources, e.g., data compression [6], resource multiplexing [7], and semantic communications [8].”
The Algorithm Design Manual (2020, background): “[Say17] K. Sayood.”
A Survey of Autonomous Underwater Vehicle Formation: Performance, Formation Control, and Communication Capability (2021, background): “However, since information can be compressed before transmission [168], decreasing amount of control information cannot contribute a lot to deal with band-width constraints.”
this paper (2009, neutral): “For traditional standard quality RTC, the time required to decode a frame is much shorter than the interarrival time of frames.”
Approximate Data Collection in Sensor Networks using Probabilistic Models (2006, neutral): “Modeling patterns and correlations in the data, and using them to reduce data transmission rates has been a central theme in the data compression literature [25].”