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图像美学与图像自然度之间相关性与图像质量关系的计算分析

Computational Analysis of Correlations between Image Aesthetic and Image Naturalness in the Relation with Image Quality.

作者信息

Le Quyet-Tien, Ladret Patricia, Nguyen Huu-Tuan, Caplier Alice

机构信息

Faculty of Information Technology, Vietnam Maritime University, 484 Lach Tray, Le Chan, Hai Phong 04000, Vietnam.

GIPSA Lab, Grenoble Alpes University, 11 Rue des Mathematiques, Grenoble Campus BP 46, CEDEX, F-38402 Saint Martin d'Heres, France.

出版信息

J Imaging. 2022 Jun 9;8(6):166. doi: 10.3390/jimaging8060166.

DOI:10.3390/jimaging8060166
PMID:35735965
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9224894/
Abstract

The main purpose of this paper is the study of the correlations between Image Aesthetic (IA) and Image Naturalness (IN) and the analysis of the influence of IA and IN on Image Quality (IQ) in different contexts. The first contribution is a study about the potential relationships between IA and IN. For that study, two sub-questions are considered. The first one is to validate the idea that IA and IN are not correlated to each other. The second one is about the influence of IA and IN features on Image Naturalness Assessment (INA) and Image Aesthetic Assessment (IAA), respectively. Secondly, it is obvious that IQ is related to IA and IN, but the exact influence of IA and IN on IQ has not been evaluated. Besides that, the context impact on those influences has not been clarified, so the second contribution is to investigate the influence of IA and IN on IQ in different contexts. The results obtained from rigorous experiments prove that although there are moderate and weak correlations between IA and IN, they are still two different components of IQ. It also appears that viewers' IQ perception is affected by some contextual factors, and the influence of IA and IN on IQ depends on the considered context.

摘要

本文的主要目的是研究图像美学(IA)与图像自然度(IN)之间的相关性,并分析在不同情境下IA和IN对图像质量(IQ)的影响。第一项贡献是关于IA与IN之间潜在关系的研究。对于该研究,考虑了两个子问题。第一个问题是验证IA和IN彼此不相关的观点。第二个问题分别是关于IA和IN特征对图像自然度评估(INA)和图像美学评估(IAA)的影响。其次,很明显IQ与IA和IN相关,但IA和IN对IQ的确切影响尚未评估。除此之外,情境对这些影响的作用尚未阐明,因此第二项贡献是研究在不同情境下IA和IN对IQ的影响。从严格实验中获得的结果证明,尽管IA和IN之间存在中度和弱相关性,但它们仍然是IQ的两个不同组成部分。还发现观看者的IQ感知受一些情境因素影响,并且IA和IN对IQ的影响取决于所考虑的情境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff49/9224894/12e99da5a224/jimaging-08-00166-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff49/9224894/12e99da5a224/jimaging-08-00166-g014.jpg

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本文引用的文献

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KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment.KonIQ-10k:一个用于盲图像质量评估深度学习的具有生态有效性的数据库。
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Reduced-reference image quality assessment by structural similarity estimation.基于结构相似性估计的降质图像质量评估。
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Optimizing a tone curve for backward-compatible high dynamic range image and video compression.优化用于向后兼容的高动态范围图像和视频压缩的色调曲线。
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