Adam Bald Eagle optimization enabled transfer learning for underwater image fusion

ABSTRACT

In this paper, a clear underwater image is attained by a fusion process using Transfer Learning (TL). Two images are selected from the underwater colour image dataset and those images are allowed to Discrete Wavelet Transform (DWT), Tetrolet transform and Saliency maps. Here, the outputs gained from images by the Tetrolet transform are fused and allowed for inverse Tetrolet transform. Moreover, the DWT process done with two images is fused and the output gained is allowed for inverse DWT. Similarly, the same fusion process is carried out with image outputs from Saliency maps. Finally, three image outputs that are considered as input to TL with newly devised optimization. Here, Convolutional Neural Network (CNN) is used with hyperparameters from trained models, such as SqueezeNet and AlexNet, where weights are updated using Adam Based Bald Eagle Algorithm (ABBEA). This ABBEA is obtained by combining the Bald Eagle Search (BES) algorithm and Adam Algorithm. Further, the ABBEA has Peak Signal-to-Noise Ratio (PSNR) with maximal of 38.95, Mean Squared Error (MSE) with lesser value of 20.14, Structural Similarity Index Measure (SSIM) with maximal value of 0.92, Mutual Information (MI) with maximal value of 0.86, Signal-to-Noise Ratio (SNR) with lesser value of 0.38.

KEYWORDS:

• SqueezeNet
• Bald Eagle Search algorithm
• AlexNet
• Adam algorithm
• Discrete Wavelet Transform
• Convolutional Neural Network
• Transfer Learning
• SqueezeNet

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Devika Sarath

Devika Sarath is a research student in Noorul Islam Centre for Higher Education in the department of Electronics and Communication Engineering, Kumaracoil, TamilNadu. Her research area is underwater communication and under water image processing. She mainly focus on Fusion of underwater images using deep learning technology.

Sucharitha M

Dr. Sucharitha M is working as Associate Professor in VIT-AP University, Andhra Pradesh, India. She holds a PhD in Image Processing and her area of research is in medical imaging, machine learning and Deep learning.