No reference image quality assessment metric based on regional mutual information among images
This work addresses the need for automatic image quality evaluation in daily camera use, but it appears incremental as it builds on existing mutual information methods with specific improvements.
The authors tackled the problem of automatic no-reference image quality assessment by proposing a new technique based on regional mutual information, which showed superiority for high-quality images and comparable performance for others on four natural and one synthetic benchmark databases.
With the inclusion of camera in daily life, an automatic no reference image quality evaluation index is required for automatic classification of images. The present manuscripts proposes a new No Reference Regional Mutual Information based technique for evaluating the quality of an image. We use regional mutual information on subsets of the complete image. Proposed technique is tested on four benchmark natural image databases, and one benchmark synthetic database. A comparative analysis with classical and state-of-art methods indicate superiority of the present technique for high quality images and comparable for other images of the respective databases.