Efficient point cloud lossless data compression method based on an embedded Gray code structured light pattern sequence

A new compression algorithm used to ensure a modified Baptista symmetric cryptosystem which is based on a chaotic dynamical system to be applicable is proposed. The Baptista symmetric cryptosystem able to produce various ciphers responding to the same message input. This modified Baptista type cryptosystem suffers from message expansion that goes against the conventional methodology of a symmetric cryptosystem. A new lossless data compression algorithm based on theideas from the Huffman coding for data transmission is proposed.This new compression mechanism does not face the problem of mapping elements from a domain which is much larger than its range.Our new algorithm circumvent this problem via a pre-defined codeword list. The purposed algorithm has fast encoding and decoding mechanism and proven analytically to be a lossless data compression technique.

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A near lossless data compression method for the Geostationary Interferometric Infrared Sounder (GIIRS) based on the combination of decimation and quantization

2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) ◽

10.1109/itaic.2019.8785868 ◽

2019 ◽

Author(s):

Minzhu Yang ◽

Raul Guerra ◽

Changpei Han ◽

Jose Fco. Lopez

Keyword(s):

Data Compression ◽

Compression Method ◽

Lossless Data Compression

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A lossless data compression method for an application in high energy physics

2009 Ph.D. Research in Microelectronics and Electronics ◽

10.1109/rme.2009.5201328 ◽

2009 ◽

Author(s):

Christian Patauner ◽

Wolfgang Pribyl ◽

Alessandro Marchioro

Keyword(s):

Data Compression ◽

High Energy Physics ◽

High Energy ◽

Compression Method ◽

Lossless Data Compression ◽

Energy Physics

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Stationary Stochastic Processes and Fractal Data Compression

International Journal of Bifurcation and Chaos ◽

10.1142/s021812749700039x ◽

1997 ◽

Vol 07 (03) ◽

pp. 551-567 ◽

Cited By ~ 5

Author(s):

Michael F. Barnsley ◽

Anca Deliu ◽

Ruifeng Xie

Keyword(s):

Data Compression ◽

Iterated Function System ◽

Geometrical Approach ◽

Compression Method ◽

Compression Algorithms ◽

Piecewise Affine ◽

Affine Mappings ◽

Iterated Function ◽

Stationary Stochastic Processes ◽

Lossless Data Compression

It is shown that the invariant measure of a stationary nonatomic stochastic process yields an iterated function system with probabilities and an associated dynamical system that provide the basis for optimal lossless data compression algorithms. The theory is illustrated for the case of finite-order Markov processes: For a zero-order process, it produces the arithmetic compression method; while for higher order processes it yields dynamical systems, constructed from piecewise affine mappings from the interval [0, 1] into itself, that may be used to store information efficiently. The theory leads to a new geometrical approach to the development of compression algorithms.

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