Objective Quality Assessment of Interpolated Natural Images

• Published in: IEEE transactions on image processing Vol. 24; no. 11; pp. 4651 - 4663
• Main Authors: Yeganeh, Hojatollah, Rostami, Mohammad, Zhou Wang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Distortion; Humans; Image edge detection; image interpolation; Image Processing, Computer-Assisted - methods; Image quality; Image quality assessment; Interpolation; Lighting; Models, Theoretical; natural scene statistics; Quality; Quality assessment; Reproducibility of Results; Spatial resolution; Visualization; Image quality assessment; natural scene statistics; image interpolation
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2015.2456638

Image interpolation techniques that create high-resolution images from low-resolution (LR) images are widely used in real world applications, but how to evaluate the quality of interpolated images is not a well-resolved issue. Subjective assessment methods are useful and reliable, but are also slow and expensive. Here, we propose an objective method to assess the quality of an interpolated natural image using the available LR image as a reference. Our method adopts a natural scene statistics (NSS) framework, where image quality degradation is gauged by the deviation of its statistical features from the NSS models trained upon high-quality natural images. Two distortion measures are proposed, namely, interpolated natural image distortion (IND) and weighted IND. Validations by subjective tests show that the proposed approach performs statistically equivalent or sometimes better than an average human subject. Moreover, we demonstrate the potential application of the proposed method in parameter tuning of image interpolation algorithms.