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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Deep leaning-based hyperspectral image classification
深度倾斜 高光谱 图像分类
2023/5/4
In this talk, we will introduce some hyperspectral image classification methods based on deep learning architecture. Recently, deep learning-based hyperspectral image classification has attracted more...
HICF: A MATLAB PACKAGE FOR HYPERSPECTRAL IMAGE CLASSIFICATION AND FUSION FOR EDUCATIONAL LEARNING AND RESEARCH
Hyperspectral classification dimensionality reduction pattern recognition image fusion
2019/2/27
A significant surge has been observed with the development and research in remote sensing in recent years for hyperspectral applications in Earth observation. Subsequently, the development of software...
HYPERSPECTRAL IMAGE DENOISING USING A NONLOCAL SPECTRAL SPATIAL PRINCIPAL COMPONENT ANALYSIS
Hyperspectral Images Noise Reduction Nonlocal Similarity Spectral Spatial Information Principal Component Analysis
2018/5/14
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classi...
A HYPERSPECTRAL IMAGE CLASSIFICATION METHOD USING ISOMAP AND RVM
Hyperspectral Image Classification Manifold Learning Isometric Feature Mapping Support Vector Machines Relevance Vector Machines
2018/5/11
Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this applica...
PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON
Python Data analysis Hyperspectral imaging Image processing Machine learning Open source
2018/5/11
Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, su...
A BAND SELECTION METHOD FOR HIGH PRECISION REGISTRATION OF HYPERSPECTRAL IMAGE
Hyperspectral Image High Spatial Resolution Image Registration CRLB Theory Band Selection Algorithm
2018/5/16
During the registration of hyperspectral images and high spatial resolution images, too much bands in a hyperspectral image make it difficult to select bands with good registration performance. Terrib...
CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE
Hyperspectral imaging technology PCA, Feature bands selection SVM Identification of matter
2018/5/14
There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or ...
第四届全国成像光谱技术与应用研讨会（IEEE Workshop on Hyperspectral Image and Signal Processing）
第四届 全国成像光谱技术与应用 研讨会
2017/3/10
成像光谱技术与应用是当今科技发展的前沿领域之一，始终得到国内外遥感科研工作者的广泛关注，业已成为地球科学研究、资源与环境调查、国防建设等领域不可或缺的技术手段。近年来，随着环境与减灾卫星、天宫一号上搭载的成像光谱仪的成功应用，我国的高光谱遥感事业发展迅猛， 预计2017年我国搭载全谱段成像光谱仪的“高分五号”将发射升空，这将进一步推进我国成像光谱技术的全面发展。
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM
Hyperspectral data multiple analysis spectral reconstruction Hyperion ALI
2016/11/23
Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution. However, hype...
MULTIPLE REFLECTION EFFECTS IN NONLINEAR MIXTURE MODEL FOR HYPERSPECTRAL IMAGE ANALYSIS
Hyperspectral images Linear mixture model (LMM) Generalized bilinear model (GBM) Modified generalized bilinear model (MGBM)
2016/11/23
Hyperspectral spectrometers can record electromagnetic energy with hundreds or thousands of spectral channels. With such high spectral resolution, the spectral information has better capability for ma...
A DIVERSIFIED DEEP BELIEF NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Diversity Deep Belief Network (DBN) Hyperspectral Image Classification
2016/11/23
In recent years, researches in remote sensing demonstrated that deep architectures with multiple layers can potentially extract abstract and invariant features for better hyperspectral image classific...
EVALUATING THE INITIALIZATION METHODS OF WAVELET NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Hyperspectral Classification Wavelet Neural Networks Wavelet Networks Initialization
2016/11/23
The idea of using artificial neural network has been proven useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of cons...
HYPERSPECTRAL IMAGE KERNEL SPARSE SUBSPACE CLUSTERING WITH SPATIAL MAX POOLING OPERATION
Hyperspectral image nonlinear processing spatial max pooling SSC kernel
2016/7/28
In this paper, we present a kernel sparse subspace clustering with spatial max pooling operation (KSSC-SMP) algorithm for hyperspectral remote sensing imagery. Firstly, the feature points are mapped f...
USING A LABORATORIAL HYPERSPECTRAL IMAGE FOR THE EVALUATION OF FEATURE REDUCTION METHODS FOR THE CLASSIFICATION OF HIGH DIMENSIONAL DATA
Hyperspectral Sensing Feature Selection Feature Extraction Classification
2015/12/31
Thee rapid advances in hyperspectral sensing technology have made it possible to collect remote sensing data in hundreds of bands. However, the data analysis methods which have been successfully appli...
HYPERSPECTRAL IMAGE FEATURE EXTRACTION BASED ON GENERALIZED DISCRIMINANT ANALYSIS
Hyperspectral Image Feature Extraction Generalized Discriminant Analysis Kernel Function
2015/12/30
The hyperspectral image enriches spectrum information, so compared with panchromatic image and multispectral image; it can classify the ground target better. The feature extraction of hyperspectral im...