Image compression using adaptive variable degree variable segment length Chebyshev polynomials

I. A. Al-Jarwan; M. J. Zemerly

doi:10.1007/11499145_121

Image compression using adaptive variable degree variable segment length Chebyshev polynomials

I. A. Al-Jarwan, M. J. Zemerly

Electrical Engineering

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

2 Scopus citations

Abstract

In this paper, a new lossy image compression technique based on adaptive variable degree variable segment length Chebyshev polynomials is proposed. The main advantage of this method over JPEG is that it has a direct individual error control where the maximum error in gray level difference between the original and the reconstructed images can be specified by the user. This is a requirement for medical applications where near lossless quality is needed. The compression is achieved by representing the gray level variations across any determined section of a row or column of an image by the coefficients of a Chebyshev polynomial. The performance of the method was evaluated on a number of test images and using some quantitative measures compared to the well known JPEG compression techniques.

Original language	British English
Pages (from-to)	1196-1207
Number of pages	12
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3540
DOIs	https://doi.org/10.1007/11499145_121
State	Published - 2005
Event	14th Scandinavian Conference on Image Analysis, SCIA 2005 - Joensuu, Finland Duration: 19 Jun 2005 → 22 Jun 2005

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title = "Image compression using adaptive variable degree variable segment length Chebyshev polynomials",

abstract = "In this paper, a new lossy image compression technique based on adaptive variable degree variable segment length Chebyshev polynomials is proposed. The main advantage of this method over JPEG is that it has a direct individual error control where the maximum error in gray level difference between the original and the reconstructed images can be specified by the user. This is a requirement for medical applications where near lossless quality is needed. The compression is achieved by representing the gray level variations across any determined section of a row or column of an image by the coefficients of a Chebyshev polynomial. The performance of the method was evaluated on a number of test images and using some quantitative measures compared to the well known JPEG compression techniques.",

author = "Al-Jarwan, {I. A.} and Zemerly, {M. J.}",

year = "2005",

doi = "10.1007/11499145_121",

language = "British English",

volume = "3540",

pages = "1196--1207",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

issn = "0302-9743",

publisher = "Springer Verlag",

note = "14th Scandinavian Conference on Image Analysis, SCIA 2005 ; Conference date: 19-06-2005 Through 22-06-2005",

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Image compression using adaptive variable degree variable segment length Chebyshev polynomials. / Al-Jarwan, I. A.; Zemerly, M. J.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3540, 2005, p. 1196-1207.

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

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AU - Zemerly, M. J.

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AB - In this paper, a new lossy image compression technique based on adaptive variable degree variable segment length Chebyshev polynomials is proposed. The main advantage of this method over JPEG is that it has a direct individual error control where the maximum error in gray level difference between the original and the reconstructed images can be specified by the user. This is a requirement for medical applications where near lossless quality is needed. The compression is achieved by representing the gray level variations across any determined section of a row or column of an image by the coefficients of a Chebyshev polynomial. The performance of the method was evaluated on a number of test images and using some quantitative measures compared to the well known JPEG compression techniques.

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 14th Scandinavian Conference on Image Analysis, SCIA 2005

Y2 - 19 June 2005 through 22 June 2005

ER -

Image compression using adaptive variable degree variable segment length Chebyshev polynomials

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