Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features
Xi'an Jiaotong University · National Center for Mathematics and Interdisciplinary Sciences · +3 more institutions
Abstract
Blind image quality assessment (BIQA) aims to evaluate the perceptual quality of a distorted image without information regarding its reference image. Existing BIQA models usually predict the image quality by analyzing the image statistics in some transformed domain, e.g., in the discrete cosine transform domain or wavelet domain. Though great progress has been made in recent years, BIQA is still a very challenging task due to the lack of a reference image. Considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we propose a novel BIQA model that utilizes the joint statistics of two types of commonly used local contrast…
Citation impact
- FWCI
- 27.43
- Percentile
- 100%
- References
- 57
Authors
5Topics & keywords
- Image quality
- Scene statistics
- Artificial intelligence
- Computer science
- Pattern recognition (psychology)
- Image (mathematics)
- Contrast (vision)
- Benchmark (surveying)