A No-Reference Image Quality Assessment Metric by Multiple Characteristics of Light Field Images

• Main Authors: Liang Shan, Ping An, Chunli Meng, Xinpeng Huang, Chao Yang, Liquan Shen
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Light field images; subjective quality assessment; objective quality assessment; light field characteristics; SVR
• Online Access: https://ieeexplore.ieee.org/document/8827489/

Evaluation of light field image (LFI), especially micro-lens camera light field (LF), is a new and challenging work. The development of image quality assessment (IQA) metric of LFIs relies on the subjective quality assessment database. In this paper, we establish a perceptual quality assessment dataset consisting of 240 distorted images from 8 source images with five distortion types. Furthermore, a no-reference IQA metric is proposed by combining 2D and 3D characteristics of LFI with the Support Vector Regression (SVR) model. The performance of the proposed metric is demonstrated by comparing with some classical full reference IQA metrics both on the presented dataset and a third-party dataset. The experiment results show that our method has a better performance than others.