Singular value thresholding for denoising time-resolved microscopy

Signal and image denoising using quantum adaptive transformation.

Video Denoising using Low Rank Matrix completion

Denoising by Quantum Interactive Patches

An Autoencoder Model to Create New Data Using Noisy and Denoised Images Corrupted by the Speckle, Gaussian, Poisson, and impulse Noise.

This Matlab code is used to add the Poisson Noise to images.

Implementation of architectures presented in "Deep Neural Networks for Low-resolution Photon-limited Imaging"

This project focuses on enhancing brain CT scans by reducing acquisition noise using a CNN-based autoencoder, followed by tumor detection on the refined image

A C++ implementation of SK-tau-ROCK methods for stochastic chemical kinetics

SCRNet is a deep neural network architecture designed to handle compressed and noisy character images signals. Tailored for tasks like character recognition and image signal restoration, SCRNet integrates classification and reconstruction pathways, enhancing performance and robustness through their synergistic interaction

Comparison of principles for the selection of the regularization parameter in image restoration variational models under Poisson degradation.

[m1ds][project] Hyperspectral unmixing with Poisson noise