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Hyperspectral Unmixing
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Hyperspectral Unmixing is a procedure that decomposes the measured pixel spectrum of hyperspectral data into a collection of constituent spectral signatures (or endmembers) and a set of corresponding fractional abundances. Hyperspectral Unmixing techniques have been widely used for a variety of applications, such as mineral mapping and land-cover change detection.
Source: An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/behnoodrasti/hysupp
공식 코드https://github.com/danfenghong/IEEE_TNNLS_EGU-Net
공식 코드https://github.com/hongmingli1995/ddica
공식 코드Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing
https://github.com/inria-thoth/edaa
공식 코드Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing
https://github.com/johnjaniczek/InfraRender
공식 코드Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model
https://github.com/mabdolali/maxvol_dual
공식 코드Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization
https://github.com/mdi-tokyotech/towards_robust_hyperspectral_unmixing_mixed_noise_modeling_and_image-domain_regularization
공식 코드Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization
https://github.com/mhmdjouni/multihu-td-matlab
공식 코드MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
https://github.com/mhmdjouni/multihu-td-python
공식 코드MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
https://github.com/pmelchior/proxmin
공식 코드https://github.com/preetam22n/deeptrans-hsu
공식 코드https://github.com/ricardoborsoi/IDNet_release
공식 코드Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
https://github.com/ricardoborsoi/redsunn
공식 코드Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks
https://github.com/roozbehrajabi/mlnmf
공식 코드Spectral Unmixing of Hyperspectral Imagery using Multilayer NMF
https://github.com/savasozkan/dscn
공식 코드Deep Spectral Convolution Network for HyperSpectral Unmixing
https://github.com/savasozkan/endnet
공식 코드EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing
https://github.com/xiuheng-wang/Plug_and_Play_HSI_unmixing
공식 코드https://github.com/xiuheng-wang/awesome-hyperspectral-image-unmixing
공식 코드Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing
https://github.com/zbzhzhy/PZRes-Net
공식 코드Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning
https://github.com/zhouyuanzxcv/Hyperspectral
공식 코드A Gaussian mixture model representation of endmember variability in hyperspectral unmixing
https://gitlab.com/nnadisic/smoothed-separable-nmf
공식 코드https://github.com/fred3m/scarlet
https://github.com/gcmshadow/proxmin
https://github.com/neel-dey/robust-nmf
Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization
https://github.com/talesimbiriba/ULTRA-V
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral Variability
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.