Image enhancement using wavelet-domain mixture models

Fei Shi, Ivan Selesnick, Onur Guleryuz

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

Abstract

We propose a non-linear mapping function for digital image enhancement in fhe wavelet domain, which amplifies midrange coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results.

Original languageEnglish (US)
Title of host publication2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop
Pages590-595
Number of pages6
DOIs
StatePublished - 2006
Event2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS - Moose, WY, United States
Duration: Sep 24 2006Sep 27 2006

Other

Other2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS
CountryUnited States
CityMoose, WY
Period9/24/069/27/06

Fingerprint

Image enhancement
Amplification
Statistical Models

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Shi, F., Selesnick, I., & Guleryuz, O. (2006). Image enhancement using wavelet-domain mixture models. In 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop (pp. 590-595). [4041133] https://doi.org/10.1109/DSPWS.2006.265492

Image enhancement using wavelet-domain mixture models. / Shi, Fei; Selesnick, Ivan; Guleryuz, Onur.

2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop. 2006. p. 590-595 4041133.

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

Shi, F, Selesnick, I & Guleryuz, O 2006, Image enhancement using wavelet-domain mixture models. in 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop., 4041133, pp. 590-595, 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS, Moose, WY, United States, 9/24/06. https://doi.org/10.1109/DSPWS.2006.265492
Shi F, Selesnick I, Guleryuz O. Image enhancement using wavelet-domain mixture models. In 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop. 2006. p. 590-595. 4041133 https://doi.org/10.1109/DSPWS.2006.265492
Shi, Fei ; Selesnick, Ivan ; Guleryuz, Onur. / Image enhancement using wavelet-domain mixture models. 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop. 2006. pp. 590-595
@inproceedings{5af19c8e5cb24a67a2749847e2ad87e6,
title = "Image enhancement using wavelet-domain mixture models",
abstract = "We propose a non-linear mapping function for digital image enhancement in fhe wavelet domain, which amplifies midrange coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results.",
author = "Fei Shi and Ivan Selesnick and Onur Guleryuz",
year = "2006",
doi = "10.1109/DSPWS.2006.265492",
language = "English (US)",
pages = "590--595",
booktitle = "2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop",

}

TY - GEN

T1 - Image enhancement using wavelet-domain mixture models

AU - Shi, Fei

AU - Selesnick, Ivan

AU - Guleryuz, Onur

PY - 2006

Y1 - 2006

N2 - We propose a non-linear mapping function for digital image enhancement in fhe wavelet domain, which amplifies midrange coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results.

AB - We propose a non-linear mapping function for digital image enhancement in fhe wavelet domain, which amplifies midrange coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results.

UR - http://www.scopus.com/inward/record.url?scp=39049091031&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=39049091031&partnerID=8YFLogxK

U2 - 10.1109/DSPWS.2006.265492

DO - 10.1109/DSPWS.2006.265492

M3 - Conference contribution

AN - SCOPUS:39049091031

SP - 590

EP - 595

BT - 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop

ER -