The detection of peaks and valleys in a 1d-vector or 2d-array (image)

Bayesian Collaborative Denoiser for Monte Carlo Rendering

Preprocessing of diffusion MRI

Tensorflow implementation of conditional variational auto-encoder for MNIST

Software to generate 2D/3D/4D analytical phantoms and their Radon transforms (parallel beam) for image processing

This project has two parts. In part one, we use markov random field to denoise an image. In Part two, we use similar model for image segmentation.

Benchmarking Denoising Algorithms with Real Photographs

Matlab Code for "A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising, ECCV 2018".

It is a Java implementation of underwater images and videos enhancement by fusion

A deep learning approach for stripe noise removal

A Conditional Generative Adverserial Network (cGAN) was adapted for the task of source de-noising of noisy voice auditory images. The base architecture is adapted from Pix2Pix.

Denoising images with a Deep Convolutional Autoencoder - Implemented in Keras

Neural Ocean is a project that addresses the issue of growing underwater waste in oceans and seas. It offers three solutions: YoloV8 Algorithm-based underwater waste detection, a rule-based classifier for aquatic life habitat assessment, and a Machine Learning model for water classification as fit for drinking or irrigation or not fit.

Compressed sensing and denoising of images using sparse representations

These are a set of scripts to train a deep learning based SAR image despeckling method.

A tool for de-noising raster digital elevation models

We derive a fundamental property of the posterior distribution in Gaussian denoising, and use it to propose a new way for uncertainty visualization, which requires no training or fine-tuning.

(MICCAI 2022) PyTorch implementation of Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence.

Reproduction of the experiments presented in Kernel PCA and De-noising in Feature Spaces, as a project in DD2434 Machine Learning Advance Course during Winter 2016