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Deep Activation Pooling for Blind Image Quality Assessment
2018
Applied Sciences
Driven by the rapid development of digital imaging and network technologies, the opinion-unaware blind image quality assessment (BIQA) method has become an important yet very challenging task. In this paper, we design an effective novel scheme for opinion-unaware BIQA. We first utilize the convolutional maps to select high-contrast patches, and then we utilize these selected patches of pristine images to train a pristine multivariate Gaussian (PMVG) model. In the test stage, each high-contrast
doi:10.3390/app8040478
fatcat:yyjf2sgkmnffjoorjy2a6kbwui