Lapped nonlinear interpolative vector quantization and image super-resolution

David G. Sheppard; Kannan Panchapakesan; Ali Bilgin; Bobby R. Hunt; Michael W. Marcellin

Lapped nonlinear interpolative vector quantization and image super-resolution

David G. Sheppard, Kannan Panchapakesan, Ali Bilgin, Bobby R. Hunt, Michael W. Marcellin

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

Abstract

This paper presents an improved version of an algorithm designed to perform image restoration via non-linear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the encoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the non-lapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the non-linearity of the algorithm is shown to produce super-resolution in the restored images.

Original language	English (US)
Pages (from-to)	224-228
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	1
State	Published - 1998
Event	Proceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA Duration: Nov 2 1997 → Nov 5 1997

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Cite this

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title = "Lapped nonlinear interpolative vector quantization and image super-resolution",

abstract = "This paper presents an improved version of an algorithm designed to perform image restoration via non-linear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the encoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the non-lapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the non-linearity of the algorithm is shown to produce super-resolution in the restored images.",

author = "Sheppard, {David G.} and Kannan Panchapakesan and Ali Bilgin and Hunt, {Bobby R.} and Marcellin, {Michael W.}",

year = "1998",

language = "English (US)",

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journal = "Conference Record of the Asilomar Conference on Signals, Systems and Computers",

issn = "1058-6393",

publisher = "IEEE Computer Society",

note = "Proceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) ; Conference date: 02-11-1997 Through 05-11-1997",

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T1 - Lapped nonlinear interpolative vector quantization and image super-resolution

AU - Sheppard, David G.

AU - Panchapakesan, Kannan

AU - Bilgin, Ali

AU - Hunt, Bobby R.

AU - Marcellin, Michael W.

PY - 1998

Y1 - 1998

N2 - This paper presents an improved version of an algorithm designed to perform image restoration via non-linear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the encoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the non-lapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the non-linearity of the algorithm is shown to produce super-resolution in the restored images.

AB - This paper presents an improved version of an algorithm designed to perform image restoration via non-linear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the encoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the non-lapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the non-linearity of the algorithm is shown to produce super-resolution in the restored images.

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UR - http://www.scopus.com/inward/citedby.url?scp=0031674408&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0031674408

SN - 1058-6393

VL - 1

SP - 224

EP - 228

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Proceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2)

Y2 - 2 November 1997 through 5 November 1997

ER -

Lapped nonlinear interpolative vector quantization and image super-resolution

Abstract

ASJC Scopus subject areas

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