Systemic distortion analysis with deep distortion directed image quality assessment models

models. Specifically, We pre-train several image quality assessment models that target to different distortions respectively. We use multiple images as anchor to test the system. We use the pre-trained IQA models to evaluate the anchor images that have gone through the system, and explore the features about the relationship between distortion types and quality scores. To analyse multiple distortions in a system, we embed dictionary learning into the multi-label classification framework. The experimental results demonstrate that our algorithm has good effectiveness, robustness and extensibility.