Image Processing Pipeline

Image processing pipelines automate the analysis and manipulation of images, aiming to improve image quality, extract meaningful information, and facilitate downstream tasks like object detection or segmentation. Current research emphasizes optimizing pipeline components, including data-driven approaches using deep learning models (e.g., U-Net, transformers, and CNNs) and algorithm selection strategies tailored to specific image distortions or application domains (e.g., low-light enhancement, demosaicing). These advancements are crucial for diverse fields, ranging from autonomous navigation and biomedical imaging to industrial quality control and environmental monitoring, enabling efficient analysis of increasingly large and complex image datasets.