Image Frequency

Image frequency analysis is emerging as a crucial tool in computer vision, focusing on leveraging the different frequency components of images to improve various tasks. Current research emphasizes the development of models that selectively process low and high-frequency information, often using techniques like Fourier transforms, Laplacian pyramids, and frequency-based masking, within architectures such as encoder-decoder networks and diffusion models. This approach shows promise in enhancing image editing, improving the robustness of models to distribution shifts, and addressing challenges in low-light imaging and long-tailed recognition by better aligning model outputs with human perception.