Empirical evaluation of full-reference image quality metrics on MDID database
This work addresses the need for standardized evaluation of image quality metrics for researchers and practitioners in image processing, but it is incremental as it applies existing methods to a new database.
The study evaluated 32 full-reference image quality assessment metrics on the MDID database, which includes images with distortions like Gaussian noise and JPEG compression, to provide a comprehensive performance comparison.
In this study, our goal is to give a comprehensive evaluation of 32 state-of-the-art FR-IQA metrics using the recently published MDID. This database contains distorted images derived from a set of reference, pristine images using random types and levels of distortions. Specifically, Gaussian noise, Gaussian blur, contrast change, JPEG noise, and JPEG2000 noise were considered.