Explore Spatial and Channel Attention in Image Quality Assessment
- Resource Type
- Conference
- Authors
- You, Junyong; Yan, Jie
- Source
- 2022 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2022 IEEE International Conference on. :26-30 Oct, 2022
- Subject
- Computing and Processing
Signal Processing and Analysis
Image quality
Visualization
Sensitivity
Codes
Image processing
Spatial databases
Quality assessment
Contrast sensitivity
image quality assessment (IQA)
selective attention
visual mechanism
- Language
- ISSN
- 2381-8549
As a subjective concept, perceived image quality is heavily affected by visual mechanisms, e.g., selective attention and contrast sensitivity. This work proposes a lightweight attention module in image quality assessment (IQA) to simulate spatial attention and contrast sensitivity mechanisms. The attention module can extract essential information from a CNN backbone for image quality perception using two sequential attention blocks: a spatial block for mimicking selective attention in spatial domain and a channel block for contrast sensitivity. Experimental results on two large-scale publicly available IQA datasets have demonstrated promising performance of the proposed approach. The source code can be found at https://github.com/junyongyou/sca_iqa.