A reference-free underwater image quality assessment metric in frequency domain

• Published in: Signal processing. Image communication Vol. 94; p. 116218
• Main Authors: Yang, Ning, Zhong, Qihang, Li, Kun, Cong, Runmin, Zhao, Yao, Kwong, Sam
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.05.2021; Elsevier BV
• Subjects: Color measurement; Dark channel prior weighting; Datasets; Forward scattering; Frequency domain; Frequency domain analysis; Image contrast; Image degradation; Image quality; Military applications; New dataset; Quality assessment; Reference-free image quality assessment; Sharpness; Underwater; Underwater image; Visual effects; Visual perception; Frequency domain; Dark channel prior weighting; Reference-free image quality assessment; New dataset; Underwater image
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2021.116218

Owing to the complexity of the underwater environment and the limitations of imaging devices, the quality of underwater images varies differently, which may affect the practical applications in modern military, scientific research, and other fields. Thus, achieving subjective quality assessment to distinguish different qualities of underwater images has an important guiding role for subsequent tasks. In this paper, considering the underwater image degradation effect and human visual perception scheme, an effective reference-free underwater image quality assessment metric is designed by combining the colorfulness, contrast, and sharpness cues. Specifically, inspired by the different sensibility of humans to high-frequency and low-frequency information, we design a more comprehensive color measurement in spatial domain and frequency domain. In addition, for the low contrast caused by the backward scattering, we propose a dark channel prior weighted contrast measure to enhance the discrimination ability of the original contrast measurement. The sharpness measurement is used to evaluate the blur effect caused by the forward scattering of the underwater image. Finally, these three measurements are combined by the weighted summation, where the weighed coefficients are obtained by multiple linear regression. Moreover, we collect a large dataset for underwater image quality assessment for testing and evaluating different methods. Experiments on this dataset demonstrate the superior performance both qualitatively and quantitatively. •We design a color measurement in frequency domain to supplement the spatial domain metric.•We propose a dark channel prior weighted contrast measure.•An Underwater Image Quality Assessment (UWIQA) dataset is constructed.