Compressing data sets of similar images with autoregressive models

Oleg S. Pianykh; John M. Tyler; Raj Sharman

doi:10.1117/12.316549

Compressing data sets of similar images with autoregressive models

Oleg S. Pianykh
, John M. Tyler
, Raj Sharman

Management Science and Systems

Louisiana State University

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The paper demonstrates the existence of a common autoregressive (CAR) compressing transform for a class of similar images, and examines the model sensitivity with respect to translations and rotations of the similar images.

Original language	English
Pages (from-to)	49-56
Number of pages	8
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3389
DOIs	https://doi.org/10.1117/12.316549
State	Published - Jul 8 1998
Event	Hybrid Image and Signal Processing VI 1998 - Orlando, United States Duration: Apr 13 1998 → Apr 17 1998

Keywords

Autoregression
Compression ratio
Correlation
Entropy
Inter-frame lossless compression
Linear regression

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10.1117/12.316549

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title = "Compressing data sets of similar images with autoregressive models",

abstract = "The paper demonstrates the existence of a common autoregressive (CAR) compressing transform for a class of similar images, and examines the model sensitivity with respect to translations and rotations of the similar images.",

keywords = "Autoregression, Compression ratio, Correlation, Entropy, Inter-frame lossless compression, Linear regression",

author = "Pianykh, \{Oleg S.\} and Tyler, \{John M.\} and Raj Sharman",

year = "1998",

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T1 - Compressing data sets of similar images with autoregressive models

AU - Pianykh, Oleg S.

AU - Tyler, John M.

AU - Sharman, Raj

PY - 1998/7/8

Y1 - 1998/7/8

N2 - The paper demonstrates the existence of a common autoregressive (CAR) compressing transform for a class of similar images, and examines the model sensitivity with respect to translations and rotations of the similar images.

AB - The paper demonstrates the existence of a common autoregressive (CAR) compressing transform for a class of similar images, and examines the model sensitivity with respect to translations and rotations of the similar images.

KW - Autoregression

KW - Compression ratio

KW - Correlation

KW - Entropy

KW - Inter-frame lossless compression

KW - Linear regression

UR - https://www.scopus.com/pages/publications/0038823508

U2 - 10.1117/12.316549

DO - 10.1117/12.316549

M3 - Conference article

AN - SCOPUS:0038823508

SN - 0277-786X

VL - 3389

SP - 49

EP - 56

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Hybrid Image and Signal Processing VI 1998

Y2 - 13 April 1998 through 17 April 1998

ER -

Compressing data sets of similar images with autoregressive models

Abstract

Keywords

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