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2018 | OriginalPaper | Buchkapitel

Retinal Image Quality Assessment by Mean-Subtracted Contrast-Normalized Coefficients

verfasst von : Adrian Galdran, Teresa Araújo, Ana Maria Mendonça, Aurélio Campilho

Erschienen in: VipIMAGE 2017

Verlag: Springer International Publishing

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Abstract

The automatic assessment of visual quality on images of the eye fundus is an important task in retinal image analysis. A novel quality assessment technique is proposed in this paper. We propose to compute Mean-Subtracted Contrast-Normalized (MSCN) coefficients on local spatial neighborhoods of a given image and analyze their distribution. It is known that for natural images, such distribution behaves normally, while distortions of different kinds perturb this regularity. The combination of MSCN coefficients with a simple measure of local contrast allows us to design a simple but effective retinal image quality assessment algorithm that successfully discriminates between good and low-quality images, while delivering a meaningful quality score. The proposed technique is validated on a recent database of quality-labeled retinal images, obtaining results aligned with state-of-the-art approaches at a low computational cost.

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Titel: Retinal Image Quality Assessment by Mean-Subtracted Contrast-Normalized Coefficients
verfasst von: Adrian Galdran
Teresa Araújo
Ana Maria Mendonça
Aurélio Campilho
Verlag: Springer International Publishing
Buch: VipIMAGE 2017
Print ISBN: 978-3-319-68194-8

Electronic ISBN: 978-3-319-68195-5

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-68195-5_92

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