Wavelet Domain

Wavelet domain analysis is a signal processing technique that decomposes data into different frequency components, revealing underlying structures and patterns often obscured in the original data. Current research focuses on leveraging wavelet transforms within various machine learning models, including convolutional neural networks and diffusion models, to improve performance in tasks such as image denoising, ground-roll separation in seismic data, and 3D shape generation. This approach offers advantages in computational efficiency, noise reduction, and feature extraction, impacting diverse fields from medical imaging and biometric authentication to video processing and speech synthesis.