19 August 2017 Blind image quality assessment based on aesthetic and statistical quality-aware features
Author Affiliations +
Abstract
The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.
© 2017 SPIE and IS&T
Mohsen Jenadeleh, Mohsen Jenadeleh, Mohammad M. Masaeli, Mohammad M. Masaeli, Mohsen E. Moghaddam, Mohsen E. Moghaddam, } "Blind image quality assessment based on aesthetic and statistical quality-aware features," Journal of Electronic Imaging 26(4), 043018 (19 August 2017). https://doi.org/10.1117/1.JEI.26.4.043018 . Submission: Received: 22 December 2016; Accepted: 20 July 2017
Received: 22 December 2016; Accepted: 20 July 2017; Published: 19 August 2017
JOURNAL ARTICLE
24 PAGES


SHARE
RELATED CONTENT

SPCA a no reference image quality assessment based on...
Proceedings of SPIE (February 03 2013)
Region-based indexing in the JPEG2000 framework
Proceedings of SPIE (July 19 2001)
A no reference image quality metric for blur and ringing...
Proceedings of SPIE (January 24 2012)
Social image quality
Proceedings of SPIE (January 24 2011)
JPEG vs. JPEG 2000 an objective comparison of image...
Proceedings of SPIE (November 01 2004)

Back to Top