Towards Effective Noise Removal and Visual Enhancement Using CILA-SegNet for Color Casting and Illumination Distortions in Underwater Images
A deep learning based framework using MSRCC-Net by adding Adaptive Feature Decoupling Module (AFDM) and Hierarchical Feature Encoder (HFE) as novelty to correct color imbalance while simultaneously normalizing illumination variations and produces visually coherent, high-quality underwater images suitable for real-world operational use.