279 citations · 559 across the 12 of their papers we have counts for
5 papers · 1 filter
Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey
Feiyun Zhu
Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrain…
Accurate Urban Road Centerline Extraction from VHR Imagery via Multiscale Segmentation and Tensor Voting
Guangliang Cheng, Feiyun Zhu, Shiming Xiang +1
It is very useful and increasingly popular to extract accurate road centerlines from very-high-resolution (VHR) re- mote sensing imagery for various applications, such as road map…
Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity
Feiyun Zhu, Ying Wang, Bin Fan +2
Hyperspectral unmixing (HU) plays a fundamental role in a wide range of hyperspectral applications. It is still challenging due to the common presence of outlier channels and the l…
Spectral Unmixing via Data-guided Sparsity
Feiyun Zhu, Ying Wang, Bin Fan +3
Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral…
Robust Hyperspectral Unmixing with Correntropy based Metric
Ying Wang, Chunhong Pan, Shiming Xiang +1
Hyperspectral unmixing is one of the crucial steps for many hyperspectral applications. The problem of hyperspectral unmixing has proven to be a difficult task in unsupervised work…