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Hyperspectral unmixing is an important technique for estimating fraction of different land cover types from remote sensing imagery. In recent years, nonnegative matrix factorization (NMF) with various constraints have been introduced into hyperspectral unmixing. Among these methods, graph based constraint have been proved to be useful in capturing the(More)
Hyperspectral unmixing is an important technique for estimating fractions of various materials from remote sensing imagery. Most unmixing methods make the assumption that no prior knowledge of endmembers is available before the estimation. This is, however, not true for some unmixing tasks for which part of the endmember signatures may be known in advance.(More)
Hyperspectral unmixing is one of the most important techniques in the remote sensing image analysis. In recent years, the nonnegative matrix factorization (NMF) method is widely used in hyperspectral unmixing. In order to solve the nonconvex problem of the NMF method, a number of constraints have been introduced into NMF models, including sparsity,(More)
Optimal designing of the water distribution network is a multi-variable optimization problem. Due to the problem of the water distribution network, an ant colony optimization (ACO) method is proposed for designing the network. The proposed ACO set the penalty function for each node and the conversion cost of the water distribution network for goal to(More)
Given a hyperspectral image, unmixing tries to estimate the spectral responses of the latent constituent materials and their corresponding fractions. Recently, Nonnegative Matrix Factorization (NMF) has been widely applied to solve the hyper-spectral unmixing problem because of its plausible physical interpretation. In this paper, we propose a novel method,(More)
Hyperspectral unmixing is an important technique for identifying the constituent spectra and estimating their corresponding fractions in an image. Nonnegative Matrix Factorization (NMF) has recently been widely used for hyperspectral unmixing. However, due to the complex distribution of hyperspectral data, most existing NMF algorithms cannot adequately(More)
This paper builds a multi-body dynamic model of an asymmetric variable sweep morphing aircraft and explores the idea of aircraft roll control by using asymmetric wing sweep angle change. This morphing aircraft is treated as a multi-body system because the large motion of wing segments makes the rigid-body approximation inadequate. Kane's method is used to(More)
Objective To find a new algorithm for PET/CT image fusion. Methods A variational model was used based on the wavelet transform. Firstly, PET and CT images were decomposed using wavelet transform. Then, images in approximate channel and detail channel were fused according to the two proposed assumption. Finally, decomposed images were synthesized to form(More)
Hyperspectral unmixing is an important technique for estimating fraction of different land covers from remote sensing imagery. In recent years, nonnegative matrix factorization (NMF) methods with various constraints have been introduced into hyperspectral unmixing. Among these methods, graph based constraint has been proved to be useful in capturing the(More)
Joint spectral-spatial information based classification is an active topic in hyperspectral remote sensing. Current classification approaches adopt a random sampling strategy to evaluate the performance of various classification systems. Due to the limitation of benchmark data, sampling of training and testing data is performed on the same image. In this(More)