No-reference image quality assessment through interactive neuroevolution

Abstract

Image quality assessment is a complex problem due to subjective nature of human visual perception. One of possible ways to take into consideration user's subjectivism is to develop interactive system which could learn the properties of user's visual perception. In this paper we present a novel way to do this via interactive neuroevolution approach. The key feature of this approach is training of artificial neural network to evaluate image quality on the base of interaction with user. Obtained solutions can then be used for image quality assessment for various automated image and video processing techniques.

Original language	English
Title of host publication	GraphiCon 2007 - International Conference on Computer Graphics and Vision, Proceedings
Publication status	Published - 2007
Event	17th International Conference on Computer Graphics and Vision, GraphiCon 2007 - Moscow, Russian Federation Duration: 23 Jun 2007 → 27 Jun 2007

Other

Other	17th International Conference on Computer Graphics and Vision, GraphiCon 2007
Country	Russian Federation
City	Moscow
Period	23.6.07 → 27.6.07

Keywords

Image quality assessment
Interactive evolution
Neuroevolution

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Vision and Pattern Recognition

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title = "No-reference image quality assessment through interactive neuroevolution",

abstract = "Image quality assessment is a complex problem due to subjective nature of human visual perception. One of possible ways to take into consideration user's subjectivism is to develop interactive system which could learn the properties of user's visual perception. In this paper we present a novel way to do this via interactive neuroevolution approach. The key feature of this approach is training of artificial neural network to evaluate image quality on the base of interaction with user. Obtained solutions can then be used for image quality assessment for various automated image and video processing techniques.",

keywords = "Image quality assessment, Interactive evolution, Neuroevolution",

author = "Tsoy, {Yury R.} and Spitsyn, {Vladimir G.} and Chernyavsky, {Alexander V.}",

year = "2007",

language = "English",

booktitle = "GraphiCon 2007 - International Conference on Computer Graphics and Vision, Proceedings",

note = "17th International Conference on Computer Graphics and Vision, GraphiCon 2007 ; Conference date: 23-06-2007 Through 27-06-2007",

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T1 - No-reference image quality assessment through interactive neuroevolution

AU - Tsoy, Yury R.

AU - Spitsyn, Vladimir G.

AU - Chernyavsky, Alexander V.

PY - 2007

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N2 - Image quality assessment is a complex problem due to subjective nature of human visual perception. One of possible ways to take into consideration user's subjectivism is to develop interactive system which could learn the properties of user's visual perception. In this paper we present a novel way to do this via interactive neuroevolution approach. The key feature of this approach is training of artificial neural network to evaluate image quality on the base of interaction with user. Obtained solutions can then be used for image quality assessment for various automated image and video processing techniques.

AB - Image quality assessment is a complex problem due to subjective nature of human visual perception. One of possible ways to take into consideration user's subjectivism is to develop interactive system which could learn the properties of user's visual perception. In this paper we present a novel way to do this via interactive neuroevolution approach. The key feature of this approach is training of artificial neural network to evaluate image quality on the base of interaction with user. Obtained solutions can then be used for image quality assessment for various automated image and video processing techniques.

KW - Image quality assessment

KW - Interactive evolution

KW - Neuroevolution

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BT - GraphiCon 2007 - International Conference on Computer Graphics and Vision, Proceedings

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Y2 - 23 June 2007 through 27 June 2007

ER -