Researchers develop a multiscale feature modulation network for advanced underwater image enhancement

The MFMN network structure. Credit: Wang Liuyi

Researchers led by Prof. Wang Rujing from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences developed a simple and effective multi-scale feature modulation network for underwater image enhancement.

Their study, published in the Journal of King Saud University—Computer and Information Sciences, addresses the challenge of improving image quality in underwater environments while considering the limitations of devices with low memory and computational power.
High-quality images are important for many underwater applications, including fisheries monitoring and environmental and species conservation. However, most deep learning-based underwater image enhancement networks are …

Be the first to comment

Leave a Reply

Your email address will not be published.