19 datasets found

The patch ordering method for image denoising uses √n by √n overlapping image patches.

The dataset used in this paper for contrast estimation and image denoising in cryo-electron microscopy.

The MNIST dataset is a large dataset of handwritten digits, and the Caltech101 Silhouettes dataset is a dataset of binary silhouettes of objects.

The Urban100 dataset is a benchmark for image denoising, containing 100 images with varying levels of noise.

The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.

The dataset used in the paper is McMaster, a dataset for image denoising.

The dataset used in the paper for image denoising and image restoration tasks.

The DND dataset contains ∼1000 pairs of clean and noisy images of consumer cameras.

The SIDD dataset contains ∼1000 pairs of clean and noisy images of smartphone cameras.

The AbdomenCT-1K dataset comprises more than 1000 abdominal CT scans aggregated from 6 existing datasets.

The dataset used in the paper is Kodak24, a dataset for image denoising.

The dataset used for training and testing the proposed method for image denoising.

The dataset used for training and testing the proposed method for image denoising.

A non-local algorithm for image denoising.

Multiplicative noise widely exists in radar images, medical images and other important fields' images. The removal of multiplicative noise can help the application of various...

The dataset used in the paper is a benchmark dataset for image denoising tasks.

The dataset used in the paper is a benchmark dataset for image denoising tasks.

Implicit neural representation, which expresses an image as a continuous function rather than a discrete grid form, is widely used for image processing. The dataset used in this...

Single Image Super-Resolution (SR) aims to generate a High Resolution (HR) image I SR from a low resolution (LR) im-age I LR such that it is similar to original HR image I HR....