Exploring underwater image quality: A review of current methodologies and emerging trends

Abstract

The complex underwater environment often leads to issues such as light scattering, color distortion, structural blurring, and noise interference in underwater images, hindering accurate scene representation. Numerous algorithms have been devised for underwater image recovery and enhancement, yet their outcomes exhibit significant variability. Thus, evaluating the quality of underwater images effectively is crucial for assessing these algorithms. This paper provides an overview of research on Underwater Image Quality Assessment (UIQA) by examining its methodologies, challenges, and future trends. Initially, the imaging principle of underwater images is introduced to summarize the primary factors affecting their quality. Subsequently, publicly available underwater image databases and UIQA methods are systematically classified and analyzed. Furthermore, extensive experimental comparisons are conducted to evaluate the performance of published quality assessment algorithms and discuss the relationship between perceived quality and utility in underwater images. Lastly, future trends in UIQA research are anticipated.