Decision Fusion for Image Quality Assessment using an Optimization Approach
Mariusz Oszust · IEEE Signal Processing Letters · 2015
The proliferation of electronic means of communication entails distortion of visual information carried by processed images. Therefore, automatic evaluation of image perceptual quality in a way that is consistent with human perception is important. In this letter, an approach to full-reference image quality assessment (IQA) is proposed. The perceptual quality of the image is evaluated using an aggregated decision of several IQA measures. An optimization problem of designing a decision fusion of 18 IQA measures is defined and solved using a genetic algorithm. Obtained fusion strategies are evaluated on widely used large image benchmarks and compared with 32 state-of-the-art IQA approaches. Results of comparison reveal that the proposed approach outperforms other competing techniques.