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arXiv.org e-Print Archive
Preprint . 2021
Data sources: arXiv.org e-Print Archive
https://dx.doi.org/10.48550/ar...
Article . 2021
License: CC BY NC SA
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A New Lossless Data Compression Algorithm Exploiting Positional Redundancy

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Jan 2021Embargo end date: 01 Jan 2021Publisher:arXiv
Authors: Venkatram, Pranav;

doi: 10.48550/arxiv.2107.13801

arXiv: 2107.13801

A New Lossless Data Compression Algorithm Exploiting Positional Redundancy

Abstract

A new run length encoding algorithm for lossless data compression that exploits positional redundancy by representing data in a two-dimensional model of concentric circles is presented. This visual transform enables detection of runs (each of a different character) in which runs need not be contiguous and hence, is a generalization of run length encoding. Its advantages and drawbacks are characterized by comparing its performance with TurboRLE.

Keywords

FOS: Computer and information sciences, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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