Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network
Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network
We propose a deep bilinear model for blind image quality assessment (BIQA) that handles both synthetic and authentic distortions. Our model consists of two convolutional neural networks (CNN), each of which specializes in one distortion scenario. For synthetic distortions, we pre-train a CNN to classify image distortion type and level, …