Differentiable fast wavelet transforms in PyTorch with GPU support.
A Discrete Fourier Transform (DFT), a Fast Wavelet Transform (FWT), and a Wavelet Packet Transform (WPT) algorithm in 1-D, 2-D, and 3-D using normalized orthogonal (orthonormal) Haar, Coiflet, Daubechie, Legendre and normalized biorthognal wavelets in Java.
Differentiable and gpu enabled fast wavelet transforms in JAX.
A refactored port and code rebuilt of JWave - Discrete Fourier Transform (DFT), Fast Wavelet Transform (FWT), Wavelet Packet Transform (WPT), some Shifting Wavelet Transform (SWT) by using orthogonal (orthonormal) wavelets like Haar, Daubechie, Coiflet, and other normalized bi-orthogonal wavelets.
An implementation of the stationary wavelet packet transform on top of PyWavelets
Implementation of different texture feature extractors and texture classifiers for both grayscale and RGB images.
DeepFix: Explainable Privacy-Preserving Image Compression for Medical Image Analysis
🖐️ Course Wavelets: Fingerprint Compression
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