<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Illumination problems have been an important concern in many image processing applications. An important issue in the field of illumination enhancement is absence of a quantitative measure for assessment of illumination of an image. In this research work a quantitative measure indicating the illumination state, i.e. contrast level and brightness of an image is also proposed. The measure utilises the estimated Gaussian distribution of the input image and the Kullback-Leibler Divergence between the estimated Gaussian distribution and the desired Gaussian distribution to calculate the quantitative measure. The experimental results show the effectiveness and the reliability of proposed illumination assessment measure.</p></abstract>

Illumination problems have been an important concern in many image processing applications. An important issue in the field of illumination enhancement is absence of a quantitative measure for assessment of illumination of an image. In this research work a quantitative measure indicating the illumination state, i.e. contrast level and brightness of an image is also proposed. The measure utilises the estimated Gaussian distribution of the input image and the Kullback-Leibler Divergence between the estimated Gaussian distribution and the desired Gaussian distribution to calculate the quantitative measure. The experimental results show the effectiveness and the reliability of proposed illumination assessment measure.

An Objective No-Reference Measure of Illumination Assessment

iCV Research Group, Institute of Technology, University of Tartu, Tartu 50411, Estonia

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"An Objective No-Reference Measure of Illumination Assessment"}

Illumination problems have been an important concern in many image processing applications. An important issue in the field of illumination enhancement is...

An Objective No-Reference Measure of Illumination Assessment

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 319 - 322

Eingereicht: 10. Juni 2015

Akzeptiert: 02. Dez. 2015

DOI: https://doi.org/10.1515/msr-2015-0043

Schlüsselwörter
Illumination assessment measure, quantitative image assessment, Kullback-Leibler divergence, image enhancement, measurement

© by Gholamreza Anbarjafari

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

An Objective No-Reference Measure of Illumination Assessment

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 319 - 322

Eingereicht: 10. Juni 2015

Akzeptiert: 02. Dez. 2015

DOI: https://doi.org/10.1515/msr-2015-0043

SchlüsselwörterIllumination assessment measure, quantitative image assessment, Kullback-Leibler divergence, image enhancement, measurement

© by Gholamreza Anbarjafari

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Illumination assessment measure, quantitative image assessment, Kullback-Leibler divergence, image enhancement, measurement