Spatial Frequency

Spatial frequency analysis examines the distribution of visual information across different frequencies, aiming to improve image processing and understanding. Current research focuses on integrating spatial and frequency domain information within deep learning models, employing architectures like transformers and convolutional neural networks, often incorporating attention mechanisms for efficient feature extraction and fusion. This approach enhances various applications, including medical image segmentation, object detection in high-resolution images, and improving the robustness of computer vision systems against adversarial attacks. The resulting advancements have significant implications for diverse fields, from medical diagnostics to remote sensing and autonomous systems.