Discrete Wavelet Transform

The Discrete Wavelet Transform (DWT) is a signal processing technique that decomposes data into different frequency components, enabling multi-scale analysis and feature extraction. Current research focuses on integrating DWT with deep learning architectures, such as convolutional neural networks (CNNs) and transformer models, to improve performance in diverse applications including image dehazing, text detection, and medical image analysis. This versatile tool significantly enhances various fields, from improving the accuracy of machine condition monitoring and deepfake detection to facilitating more efficient image processing and time series forecasting.