Image Difference

Image difference analysis focuses on identifying and characterizing variations between images, aiming to extract meaningful information from these discrepancies. Current research emphasizes leveraging deep learning architectures, such as convolutional neural networks and diffusion models, to analyze image differences for various applications, including object detection, change detection in remote sensing, and image quality assessment. This field is crucial for advancing autonomous systems, improving multimodal large language models, and enhancing image processing techniques across diverse scientific and engineering domains. The development of efficient and robust methods for image difference analysis is driving progress in numerous fields, from automated driving to medical image analysis.