Image Enhancement Techniques -- 专题文献

专题：Image Enhancement Techniques

This cluster of papers focuses on the advancements in image enhancement techniques, including dehazing, contrast enhancement, and color transfer. It covers a wide range of topics such as underwater imaging, single image restoration, low-light enhancement, and high dynamic range imaging. The cluster showcases the application of deep learning methods in addressing challenges related to image processing and enhancement.

专题：Image Enhancement Techniques

最新文献

Real-World Nighttime Image Dehazing via Bayesian-Based Fractional-Order Variational Model

When Optimal Transport Meets Photo-Realistic Image Dehazing With Unpaired Training

SGDFuse: SAM-guided diffusion model for high-fidelity infrared and visible image fusion

A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning

Vision Transformer-Based Image Dehazing for Climate-Resilient Maritime Navigation

Learning a Physical-Aware Diffusion Model Based on Transformer for Underwater Image Enhancement

IHDCP: Single Image Dehazing Using Inverted Haze Density Correction Prior

Learning Dual Modality Interactions for Event-Based Motion Deblurring

Structure-Preserving Frequency-Regularized Text-Guided Optimal Transport for Unpaired Rain Streaks and Raindrops Removal

Turbidity–Similarity Decoupling: Feature-Consistent Mutual Learning for Underwater Salient Object Detection

近5年高被引文献