Blind deconvolution of motion blur

A comparison of Median filter and Wiener filter in image restoration.

Recover blurry images using Weiner deconvolution of an image with user-defined point spread function (PSF)

Various adaptive filter implementations (university project)

Digital Image Processing Assignment solutions

Locally Adaptive Wiener Filters for Image Denoising

This repository provides a PyTorch implementation of FFDNet image denoising https://arxiv.org/abs/1710.04026. First implemented by Matias Tassano https://doi.org/10.5201/ipol.2019.231, the FFDNet source code has been adapted so as to extract cameras PRNU.

A novel approach to blind motion deblurring by converting a non-blind method (Weiner Deconvolution) to a blind method using Deep Learning

Kalman and Wiener Filter for faulty sensor interpolation.

Statistical Digital Signal Processing and Modeling

enhance and restore different types of images by using various approaches

Practices of image deblurring, image inpainting, and image classification.

Equalize audio with 4 different modes: uniform frequency-ranges equalization, animal and music sounds, vocals and instruments, and noise removal using Wiener filtering. Visualizes spectrograms, audiogram and frequency domains and saves results as WAV files.

Test of python-dask for wiener filtering in radio astronomy

Tools to analyze Planck CMB maps with a focus on thermal and kinetic SZ effect. Includes implementation of Internal Linear Combination (ILC) and Wiener filter using NIFTy. Supplementary repo to master thesis

Signal Equalizer is a Python-based application designed to process and analyze various types of signal data, including audio and ECG signals. It provides functionalities for reading, processing, visualizing, and enhancing signal data using techniques such as Wiener filtering.