Hyperspectral Image Classification

53 papers with code • 7 benchmarks • 6 datasets

Hyperspectral image classification is the task of classifying a class label to every pixel in an image that was captured using (hyper)spectral sensors.

( Image credit: Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification )

Libraries

Use these libraries to find Hyperspectral Image Classification models and implementations
3 papers
268

Most implemented papers

Going Deeper with Contextual CNN for Hyperspectral Image Classification

eecn/Hyperspectral-Classification 12 Apr 2016

The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map.

HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image

eecn/Hyperspectral-Classification 28 Feb 2018

In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral image data, called HSI-CNN.

BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image

AngryCai/BS-Nets 17 Apr 2019

The framework consists of a band attention module (BAM), which aims to explicitly model the nonlinear inter-dependencies between spectral bands, and a reconstruction network (RecNet), which is used to restore the original HSI cube from the learned informative bands, resulting in a flexible architecture.

Multitask Deep Learning with Spectral Knowledge for Hyperspectral Image Classification

stop68/remote-sensing-image-classification 11 May 2019

Deep learning models have achieved promising results on hyperspectral image classification, but their performance highly rely on sufficient labeled samples, which are scarce on hyperspectral images.

Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images

ilyakava/pyfst 17 Jun 2019

Recent developments in machine learning and signal processing have resulted in many new techniques that are able to effectively capture the intrinsic yet complex properties of hyperspectral imagery.

Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects

mahmad00/HSI-Traditional-to-Deep-Models 15 Jan 2021

Therefore, this survey discusses some strategies to improve the generalization performance of DL strategies which can provide some future guidelines.

Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNN

mahmad00/Artifacts-of-DR-on-Hybrid-CNN-for-HSIC 25 Jan 2021

Convolutional Neural Networks (CNN) has been extensively studied for Hyperspectral Image Classification (HSIC) more specifically, 2D and 3D CNN models have proved highly efficient in exploiting the spatial and spectral information of Hyperspectral Images.

SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image Classification

tanmay-ty/SpectralNET 1 Apr 2021

In this article, we propose SpectralNET, a wavelet CNN, which is a variation of 2D CNN for multi-resolution HSI classification.

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

danfenghong/IEEE_TGRS_SpectralFormer 7 Jul 2021

Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies.

BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

kaustubh0mani/BASS-Net 1 Dec 2016

Deep learning based landcover classification algorithms have recently been proposed in literature.