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Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
Danfeng Hong, Lianru Gao, Jing Yao +4
Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneous…
Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse Representations
Lina Zhuang, Lianru Gao, Bing Zhang +2
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.…
Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super-Resolution
Ke Zheng, Lianru Gao, Wenzhi Liao +4
Due to the limitations of hyperspectral imaging systems, hyperspectral imagery (HSI) often suffers from poor spatial resolution, thus hampering many applications of the imagery. Hy…
Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning
Lianru Gao, Danfeng Hong, Jing Yao +3
Extensive attention has been widely paid to enhance the spatial resolution of hyperspectral (HS) images with the aid of multispectral (MS) images in remote sensing. However, the ab…