A Study on Underwater Image Processing Techniques

Abstract

Abstract: In recent years, a potential interest has been developed in exploring and enhancing the quality of underwater images. The captured underwater images often experience scattering and high levels of noise due to the properties of light transit within the water and the biotic movement that occurs inside the ocean bottom. Underwater cameras or devices were fitted inside the unmanned underwater vehicles (UUVs), autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs), ocean detector networks, etc to see the ocean bottom. Despite being a crucial detector for keeping an eye on underwater landscapes, modern underwater camera sensors or detectors contain a number of problems. Numerous solutions to the issues with conventional underwater photography have been put out during the last five years. With the help of the number of contributions and difficulties reported by more than 40 researchers in their research article, this study focused to mention the current underwater image processing methods. This article represents an overview of numerous underwater image-processing techniques utilized, including underwater picture de-scattering, underwater image colour refurbishment, and underwater image aspect evaluations. Also, the latest trends, problems, and challenges for creating and processing underwater image sensors were discussed. objective: analysis of underwater image processing using numerous techniques method: The two kinds of underwater picture de-scattering techniques—hardware-based and software-based—are initially reviewed in this work. Then, we list four common techniques for restoring the colour of underwater images. We then discuss reference-based indexes and non-reference indexes, two techniques for evaluating the quality of underwater images. We conclude by summarising this essay and discussing potential directions for this area. result: Experimental Results of Fluorescence Imaging Underwater Polarization Imaging Experimental Results of Traditional Physical Model-based Methods. Experimental Results of Traditional Non-physical Model-based Methods. Experimental Results of Color Restoration Methods conclusion: We provided a thorough analysis of underwater image processing in this study. According to the different imaging kinds, we separated the underwater image processing techniques into two groups. The two courses' cutting-edge methods were thoroughly debated and critiqued. The wavelength compensation technique, including physical model, non-physical model, and colour reconstruction approach are presented for software-based underwater image processing. Finally, a summary of future trends and quality evaluation techniques is provided