Blind multiply distorted image quality assessment using an ensemble random forest.
Mengzhu MaChaofeng LiPublished in: CISP-BMEI (2017)
Keyphrases
- random forest
- image quality assessment
- distorted images
- random forests
- structural similarity
- ensemble methods
- quality assessment
- decision trees
- image quality
- ensemble learning
- image database
- human visual system
- visual perception
- feature set
- ensemble classifier
- quality evaluation
- natural images
- base classifiers
- correlation coefficient
- quality measures
- human perception
- quality metrics
- kullback leibler divergence
- multi label
- natural scenes
- benchmark datasets
- high quality
- visual quality