使用人工智能和深度学习的水下摄影降噪

Sanjiv. S, K. R., R. Ranjith, A. Chandrasekar, V. K.
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引用次数: 0

摘要

水下摄像机被广泛用于观察海底。无人水下自动化、自主水下航行器和原位海洋传感器是发现它们的常见场所(auv)。虽然是跟踪水下景观的重要传感器,但最近的水下相机传感器存在几个问题。由于光线在水中的移动方式和海底的生物活动,水下照片通常充满了散射和噪音。在过去的五年中,各种各样的策略已经发展到海洋学研究的重要事实,包括图像处理和水下传感。一个先前的挑战是散射效应的光吸收,这降低了水下条件下的图像质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Underwater Photography Noise cancellation Using Artificial Intelligence and Deep Learning
Cameras submerged underwater are widely used to see the ocean floor. Unmanned underwater automation, autonomous underwater vehicles, and in situ ocean sensors are common places to find them (AUVs). While being an essential sensor for keeping track of underwater landscapes, recent underwater camera sensors have several issues. Because of how light moves through water and the biological activity at the seafloor, underwater photographs are typically cluttered with scatters and noise. Over the past five years, a variety of tactics have been developed to Important facts of oceanographic study include image processing and underwater sensing. One prior challenge is light absorption with a scattering effect, which reduces the image quality in underwater conditions with respect to its ground truth.
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