This work proposes a perceptual based no-reference objective image quality metric by integrating perceptually weighted local noise into a probability summation model. Unlike existing objective metrics, the proposed no-reference metric is able to predict the relative amount of noise perceived in images with different content, without a reference. Results are reported on both the LIVE and TID2008 databases. The proposed no-reference metric achieves consistently a good performance across noise types and across databases as compared to many of the best very recent no-reference quality metrics. The proposed metric is able to predict with high accuracy the relative amount of perceived noise in images of different content.
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Electrical and Electronic Engineering