Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper, we present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherIEEE
Pages2649-2651
Number of pages3
Volume5
StatePublished - 1998
EventProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. Part 1 (of 6) - Seattler, WA, USA
Duration: May 12 1998May 15 1998

Other

OtherProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. Part 1 (of 6)
CitySeattler, WA, USA
Period5/12/985/15/98

Fingerprint

vector quantization
Vector quantization
restoration
Restoration
Diffraction
education
diffraction
decoders
coders
counters
filters
output
simulation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics
  • Software

Cite this

Panchapakesan, K., Bilgin, A., Marcellin, M. W., & Hunt, B. R. (1998). Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 5, pp. 2649-2651). IEEE.

Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization. / Panchapakesan, Kannan; Bilgin, Ali; Marcellin, Michael W; Hunt, Bobby R.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 5 IEEE, 1998. p. 2649-2651.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Panchapakesan, K, Bilgin, A, Marcellin, MW & Hunt, BR 1998, Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. vol. 5, IEEE, pp. 2649-2651, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. Part 1 (of 6), Seattler, WA, USA, 5/12/98.
Panchapakesan K, Bilgin A, Marcellin MW, Hunt BR. Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 5. IEEE. 1998. p. 2649-2651
Panchapakesan, Kannan ; Bilgin, Ali ; Marcellin, Michael W ; Hunt, Bobby R. / Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 5 IEEE, 1998. pp. 2649-2651
@inproceedings{3bf421fa2cb449afa1ce166b611b8500,
title = "Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization",
abstract = "In this paper, we present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm.",
author = "Kannan Panchapakesan and Ali Bilgin and Marcellin, {Michael W} and Hunt, {Bobby R.}",
year = "1998",
language = "English (US)",
volume = "5",
pages = "2649--2651",
booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "IEEE",

}

TY - GEN

T1 - Joint compression and restoration of images using wavelets and non-linear interpolative vector quantization

AU - Panchapakesan, Kannan

AU - Bilgin, Ali

AU - Marcellin, Michael W

AU - Hunt, Bobby R.

PY - 1998

Y1 - 1998

N2 - In this paper, we present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm.

AB - In this paper, we present a wavelet based non-linear interpolative vector quantization scheme for joint compression and restoration of images; two tasks which are traditionally regarded as having conflicting goals. Vector quantizer codebook training is done using a training set consisting of pairs of the original image and its diffraction-limited counterpart. The designed VQ is then used to compress and simultaneously restore diffraction-limited images. Results from simulations indicate that the image produced at the output of the decoder is quantitatively and visually superior to the diffraction-limited image at the input to the encoder. We also compare the performance of several wavelet filters in our algorithm.

UR - http://www.scopus.com/inward/record.url?scp=0031632949&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031632949&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0031632949

VL - 5

SP - 2649

EP - 2651

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

PB - IEEE

ER -