What question did this study set out to answer?

To provide a comprehensive overview and standardized comparative evaluation of traditional and deep learning-based underwater optical image enhancement techniques.

March 10, 2025International Journal of Image and Data Fusion

State-of-the-art techniques for optical underwater image enhancement

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Authors

SKS. N. KumarAmal Jyothi College of Engineering SKS. KannadhasanOrthopaedic Research Group

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Implication

Comparative review evaluates classical and deep-learning image enhancement algorithms across aquatic datasets, highlighting performance trade-offs between physical models and generative networks.

Key Points

To provide a comprehensive overview and standardized comparative evaluation of traditional and deep learning-based underwater optical image enhancement techniques.
Reviewed classical methods including histogram equalization, spatial filtering, color correction, and multi-scale image fusion.
Examined deep learning architectures focusing on Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs).
Conducted qualitative and quantitative evaluations of representative enhancement algorithms using standard metrics on the HICRD dataset.
Deep learning approaches, particularly GANs and CNNs, demonstrate superior capability in recovering realistic color balance and complex textures under challenging optical conditions.
Traditional physical and fusion-based algorithms provide reliable contrast improvement and noise reduction but exhibit inconsistent performance across variable aquatic environments without parameter tuning.

Cite This Study

Kumar et al. (2025) studied this question.

synapsesocial.com/papers/6a7ec82bb71e9814536281d6 https://doi.org/10.1080/19479832.2025.2465532

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Implication

Comparative review evaluates classical and deep-learning image enhancement algorithms across aquatic datasets, highlighting performance trade-offs between physical models and generative networks.

State-of-the-art techniques for optical underwater image enhancement

Discussion

Member takes

Implication

Key Points

Cite This Study

State-of-the-art techniques for optical underwater image enhancement

Discussion

Member takes

Implication

Key Points

Cite This Study

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