Image enhancement using wavelet-domain mixture models

Fei Shi; Ivan W. Selesnick; Onur Guleryuz

doi:10.1109/DSPWS.2006.265492

Image enhancement using wavelet-domain mixture models

Fei Shi, Ivan W. Selesnick, Onur Guleryuz

Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

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 language	English (US)
Pages	590-595
Number of pages	6
DOIs	https://doi.org/10.1109/DSPWS.2006.265492
State	Published - 2006
Event	2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS - Moose, WY, United States Duration: Sep 24 2006 → Sep 27 2006

Other

Other	2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS
Country/Territory	United States
City	Moose, WY
Period	9/24/06 → 9/27/06

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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10.1109/DSPWS.2006.265492

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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 Selesnick, {Ivan W.} and Onur Guleryuz",

year = "2006",

doi = "10.1109/DSPWS.2006.265492",

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note = "2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS ; Conference date: 24-09-2006 Through 27-09-2006",

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AU - Selesnick, Ivan W.

AU - Guleryuz, Onur

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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.

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T2 - 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, DSPWS

Y2 - 24 September 2006 through 27 September 2006

ER -

Image enhancement using wavelet-domain mixture models

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