[PDF][PDF] 基于稀疏表示模型和自回归模型的高光谱分类
宋琳， 程咏梅， 赵永强 - Acta Optica Sinica, 2012 - researching.cn
摘要针对高光谱分类中对光谱信息和空间信息利用不足的问题, 提出了一种基于稀疏表示模型和
自回归模型相结合的分类算法. 该算法利用稀疏表示模型和自回归模型, 设计联合字典 …
自回归模型相结合的分类算法. 该算法利用稀疏表示模型和自回归模型, 设计联合字典 …
[PDF][PDF] 基于邻域分割的空谱联合稀疏表示高光谱图像分类技术研究
王彩玲， 王洪伟， 胡炳樑， 温佳， 徐君， 李湘眷 - 光谱学与光谱分析, 2016 - researching.cn
摘要传统的高光谱遥感影像分类算法侧重于光谱信息的应用. 随着高光谱遥感影像的空间分辨率
的增加, 高光谱影像中相同类别的地物在空间分布上呈现聚类特性, 将空间特性有效地应用于高 …
的增加, 高光谱影像中相同类别的地物在空间分布上呈现聚类特性, 将空间特性有效地应用于高 …
[HTML][HTML] 改进的联合稀疏表示算法应用于高光谱图像分类
李楚婷 - Advances in Applied Mathematics, 2020 - hanspub.org
高光谱遥感图像含有大量光谱和空间信息, 但同时存在数据冗余和噪声干扰问题.
为了解决上述问题, 本文提出一种高光谱图像分类方法: 改进的联合稀疏表示算法(A2-JSRC) …
为了解决上述问题, 本文提出一种高光谱图像分类方法: 改进的联合稀疏表示算法(A2-JSRC) …
[PDF][PDF] Relationship between the number of labeled samples and classification accuracy based on sparse representation
Q Zhou, C Zhang, Y Zhang - Proceedings of Science, 2015 - pos.sissa.it
The paradox of high dimension of hyperspectral data is that, in one hand, many
classification methods are not appropriate for dealing with high dimensional data, so …
classification methods are not appropriate for dealing with high dimensional data, so …
Special object recognition based on sparse representation in multisource data fusion samples
C Zha - Mathematical Problems in Engineering, 2020 - Wiley Online Library
Wireless sensor networks (WSNs) suffer from limited power and large amounts of redundant
data. This paper describes a multisource data fusion method for WSNs that can be …
data. This paper describes a multisource data fusion method for WSNs that can be …
Improving hyperspectral data classification of satellite imagery by using a sparse based new model with learning dictionary
C Zhang, X Hao, J Bai, M Dai - 2014 6th Workshop on …, 2014 - ieeexplore.ieee.org
Statistic classification of hyperspectral data is a great challenge because of its large number
of spectral channels, especially when the labeled training samples are relatively few. Most of …
of spectral channels, especially when the labeled training samples are relatively few. Most of …
Sparse representation based multi-threshold segmentation for hyperspectral target detection
W Feng, Q Chen, Z Miao, W He, G Gu… - … and Imaging 2013 …, 2013 - spiedigitallibrary.org
A sparse representation based multi-threshold segmentation (SRMTS) algorithm for target
detection in hyperspectral images is proposed. Benefiting from the sparse representation …
detection in hyperspectral images is proposed. Benefiting from the sparse representation …
Discriminative Eigenpixels-Based Dictionary Learning for Hyperspectral Image Classification
L Song, S Li - IEEE Geoscience and Remote Sensing Letters, 2019 - ieeexplore.ieee.org
Sparse representation (SR) model has been applied to hyperspectral image (HSI)
classification based on the observation that any spectral pixel could be approximately …
classification based on the observation that any spectral pixel could be approximately …