Wavelet transforms

Wavelet transforms are mathematical tools used to analyze signals by breaking them into smaller, detailed parts at different scales or resolutions. Unlike traditional methods that look at signals as a whole, wavelets focus on both the overall structure and fine details simultaneously. This helps in identifying important features, patterns, or anomalies in data such as images, audio, or time-series signals. Think of it like zooming in and out on a picture to see both the big picture and the tiny details clearly, making wavelet transforms valuable for compression, noise reduction, and feature detection.