scholarly journals Data Processing Method Applying Principal Component Analysis and Spectral Angle Mapper for Imaging Spectroscopic Sensors

2008 ◽  
Vol 8 (7) ◽  
pp. 1310-1316 ◽  
Author(s):  
P. Beatriz Garcia-Allende ◽  
Olga M. Conde ◽  
JesÚs Mirapeix ◽  
Ana M. Cubillas ◽  
JosÉ M. Lopez-Higuera
Keyword(s):  
Principal Component Analysis ◽  
Data Processing ◽  
Principal Component ◽  
Component Analysis ◽  
Processing Method ◽  
Spectral Angle Mapper ◽  
Data Processing Method ◽  
Spectroscopic Sensors ◽  
Spectral Angle

Raman imaging and principal component analysis-based data processing on uranium oxide ceramics

2017 ◽  
Vol 129 ◽  
pp. 260-269 ◽  
Author(s):  
O.A. Maslova ◽  
G. Guimbretière ◽  
M.R. Ammar ◽  
L. Desgranges ◽  
C. Jégou ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Data Processing ◽  
Uranium Oxide ◽  
Principal Component ◽  
Component Analysis ◽  
Raman Imaging ◽  
Oxide Ceramics

Object Classification via PCANet and Color Constancy Model

2014 ◽  
Vol 635-637 ◽  
pp. 997-1000 ◽  
Author(s):  
De Kun Hu ◽  
Li Zhang ◽  
Wei Dong Zhao ◽  
Tao Yan
Keyword(s):  
Principal Component Analysis ◽  
Data Processing ◽  
Functional Properties ◽  
Principle Component Analysis ◽  
Color Constancy ◽  
Principal Component ◽  
Object Classification ◽  
Component Analysis ◽  
Color Images ◽  
Principle Component

In order to classify the objects in nature images, a model with color constancy and principle component analysis network (PCANet) is proposed. The new color constancy model imitates the functional properties of the HVS from the retina to the double-opponent cells in V1. PCANet can be designed and learned extremely, which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms. At last, a SVM is trained to classify the object in the image. The results of experiments demonstrate the potential of the model for object classification in wild color images.

Sign in / Sign up

Export Citation Format

Share Document