Hyperspectral Image Denoising

7 papers with code • 1 benchmarks • 0 datasets

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Most implemented papers

Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network

WHUQZhang/HSID-CNN 1 Jun 2018

Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the performance of the subsequent HSI interpretation and applications.

Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations

LinaZhuang/FastHyDe_FastHyIn 11 Mar 2021

This paper introduces two very fast and competitive hyperspectral image (HSI) restoration algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with Gaussian and Poissonian noise, and fast hyperspectral inpainting (FastHyIn), an inpainting algorithm to restore HSIs where some observations from known pixels in some known bands are missing.

3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

Vandermode/QRNN3D 10 Mar 2020

In this paper, we propose an alternating directional 3D quasi-recurrent neural network for hyperspectral image (HSI) denoising, which can effectively embed the domain knowledge -- structural spatio-spectral correlation and global correlation along spectrum.

Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix Approximation

jingweisong/uncertainty-estimation-for-hyper-spectral-image-denoising 23 Apr 2020

Sliding-window based low-rank matrix approximation (LRMA) is a technique widely used in hyperspectral images (HSIs) denoising or completion.

Hyperspectral Image Denoising With Realistic Data

colintaozhang/hsidwrd ICCV 2021

On the other hand, we propose an accurate HSI noise model which matches the distribution of real data well and can be employed to synthesize realistic dataset.

Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse Representations

LinaZhuang/RobustHyDenoiser-RhyDe- 12 Mar 2021

Hyperspectral imaging measures the amount of electromagnetic energy across the instantaneous field of view at a very high resolution in hundreds or thousands of spectral channels.

HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package

helmholtz-ai-energy/hyde 14 Apr 2022

Furthermore, we present a method for training DNNs for denoising HSIs which are not spatially related to the training dataset, i. e., training on ground-level HSIs for denoising HSIs with other perspectives including airborne, drone-borne, and space-borne.