Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
Xi'an Jiaotong University · Hong Kong Polytechnic University · +1 more institution
Abstract
It is an important task to faithfully evaluate the perceptual quality of output images in many applications, such as image compression, image restoration, and multimedia streaming. A good image quality assessment (IQA) model should not only deliver high quality prediction accuracy, but also be computationally efficient. The efficiency of IQA metrics is becoming particularly important due to the increasing proliferation of high-volume visual data in high-speed networks. We present a new effective and efficient IQA model, called gradient magnitude similarity deviation (GMSD). The image gradients are sensitive to image distortions, while different local structures in a distorted image suffer different degrees of…
Citation impact
- FWCI
- 69.69
- Percentile
- 100%
- References
- 44
Authors
4Topics & keywords
- Image quality
- Computer science
- Artificial intelligence
- Pooling
- Similarity (geometry)
- Computer vision
- Pattern recognition (psychology)
- Standard deviation