A content-specific IQM augmentation technique for better assessment of image quality
Navaneeth Kamballur Kottayil, Irene Cheng · 2017
In this paper, we propose a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM. We demonstrate this concept by categorizing the image content into three classes, generating and applying VEI to different IQM's and showing performance improvement in all of the cases. The performance evaluation was conducted on CSIQ dataset.