Human-Visual-System-Inspired Underwater Image Quality Measures
Tufts University · The University of Texas at San Antonio
Abstract
Underwater images suffer from blurring effects, low contrast, and grayed out colors due to the absorption and scattering effects under the water. Many image enhancement algorithms for improving the visual quality of underwater images have been developed. Unfortunately, no well-accepted objective measure exists that can evaluate the quality of underwater images similar to human perception. Predominant underwater image processing algorithms use either a subjective evaluation, which is time consuming and biased, or a generic image quality measure, which fails to consider the properties of underwater images. To address this problem, a new nonreference underwater image quality measure (UIQM) is presented in this…
Citation impact
- FWCI
- 8.80
- Percentile
- 100%
- References
- 50
Authors
3Topics & keywords
- Underwater
- Image quality
- Computer vision
- Artificial intelligence
- Computer science
- Measure (data warehouse)
- Contrast (vision)
- Human visual system model
- Life below water