Adaptable Image Quality Assessment Using Meta-Reinforcement Learning of Task Amenability.
Shaheer U. SaeedYunguan FuVasilis StavrinidesZachary M. C. BaumQianye YangMirabela RusuRichard E. FanGeoffrey A. SonnJ. Alison NobleDean C. BarrattYipeng HuPublished in: ASMUS@MICCAI (2021)
Keyphrases
- image quality assessment
- reinforcement learning
- structural similarity
- quality assessment
- image quality
- image database
- natural scene statistics
- natural images
- image quality measures
- structural similarity index
- image quality metrics
- correlation coefficient
- human visual system
- human perception
- reduced reference
- machine learning
- quality measures
- quality evaluation
- kullback leibler divergence
- quality metrics
- distorted images
- blind image quality assessment
- similarity index
- natural scenes
- structural information
- visual perception
- region of interest
- eye tracking
- perceptual image quality
- high frequency