Enhancement of Underwater Video through Adaptive Fuzzy Weight Evaluation

Jitendra Sonawane, Mukesh Patil, Gajanan K Birajdar

Abstract


Underwater video enhancement plays a critical role in improving the visibility and quality of underwater imagery, which is essential for various applications such as marine biology, underwater archaeology, and offshore inspection. In this article, we present a novel approach for enhancing underwater videos. Our method employs fuzzy logic and a unique fuzzy channel weight coefficient to effectively address challenges in underwater imaging. The method aims to improve the perceptual quality of underwater videos by enhancing contrast, reducing noise, and increasing overall image clarity. The key component in our approach is the integration of fuzzy logic based channel weight coefficient which is adaptively selected to enhance the video frames. The fuzzy channel weight coefficient-based method assigns weights to different color channels in a manner that optimally addresses the underwater imaging conditions. To evaluate the performance of our fuzzy enhancement algorithm, we conducted experiments on the Fish4Knowledge database, a widely used benchmark dataset for underwater video analysis. We quantitatively assessed the improvement in video quality using various metrics, including Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Structural Similarity Index (SSIM), and entropy. Our results demonstrate that the proposed fuzzy logic-based enhancement method outperforms existing techniques in terms of video quality enhancement and underwater image correction in terms of PSNR, RMSE and SSIM.

Keywords


Underwater Video Enhancement; Adaptive Weight Assignment; Adaptive Contrast Enhancement; Fuzzy Logic; Fuzzy Interference System (FIS); Membership Function.

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References


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DOI: https://doi.org/10.18196/jrc.v5i2.20496

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