An Underwater Image Quality Assessment Metric

• Published in: IEEE transactions on multimedia Vol. 25; pp. 5093 - 5106
• Main Authors: Guo, Pengfei, Liu, Hantao, Zeng, Delu, Xiang, Tao, Li, Leida, Gu, Ke
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Benchmark testing; Benchmarks; Distortion measurement; enhancement; human visual system; Image color analysis; Image enhancement; Image quality; Measurement; objective metric; Performance prediction; Quality assessment; Quality management; Underwater; Visual systems
• ISSN: 1520-9210; 1941-0077
• DOI: 10.1109/TMM.2022.3187212

Various image enhancement algorithms are adopted to improve underwater images that often suffer from visual distortions. It is critical to assess the output quality of underwater images undergoing enhancement algorithms, and use the results to optimise underwater imaging systems. In our previous study, we created a benchmark for quality assessment of underwater image enhancement via subjective experiments. Building on the benchmark, this paper proposes a new objective metric that can automatically assess the output quality of image enhancement, namely UWEQM. By characterising specific underwater physics and relevant properties of the human visual system, image quality attributes are computed and combined to yield an overall metric. Experimental results show that the proposed UWEQM metric yields good performance in predicting image quality as perceived by human subjects.