Thermal Image Fusion

Thermal image fusion combines information from visual and thermal cameras to create enhanced images with improved detail and information content, primarily aiming to overcome limitations of individual sensor modalities. Current research emphasizes deep learning approaches, particularly convolutional neural networks (CNNs) and transformers, often integrated in multi-stage architectures to handle both local and global image features, and addressing challenges like image misalignment. This field is significant for applications ranging from search and rescue operations to fire safety and autonomous driving, offering improved object detection and scene understanding in challenging conditions where single-sensor data is insufficient.