Unveiling the hidden depths: advancements in underwater image enhancement using deep learning and auto-encoders.

ABSTRACT: Underwater images hold immense value for various fields, including marine biology research, underwater infrastructure inspection, and exploration activities. However, capturing high-quality images underwater proves challenging due to light absorption and scattering leading to color distortion, blue green hues. Additionally, these phenomena decrease contrast and visibility, hindering the ability to extract valuable information. Existing image enhancement methods often struggle to achieve accurate color correction while preserving crucial image details. This article proposes a novel deep learning-based approach for underwater image enhancement that leverages the power of autoencoders. Specifically, a convolutional autoencoder is trained to learn a mapping from the distorted colors present in

SUBMITTER: Bantupalli J 

PROVIDER: S-EPMC11623242 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature