scholarly journals The Principal Component Transform of Parametrized Functions

2017 ◽  
Vol 08 (04) ◽  
pp. 453-475
Author(s):  
Ilia Zabrodskii ◽  
Arcady Ponosov
Keyword(s):  
Principal Component ◽  
Principal Component Transform

Research on Fusion Approach for Hyperspectral Image and Multispectral Image of HJ-1A

2011 ◽  
Vol 356-360 ◽  
pp. 2897-2903
Author(s):  
Fen Fen Guo ◽  
Jian Rong Fan ◽  
Wen Qian Zang ◽  
Fei Liu ◽  
Huai Zhen Zhang
Keyword(s):  
Wavelet Transform ◽  
Spatial Resolution ◽  
Hyperspectral Image ◽  
3D Structure ◽  
Principal Component ◽  
Multispectral Image ◽  
Spectral Quality ◽  
Principal Component Transform ◽  
3D Wavelet Transform ◽  
Fusion Approach

The vacancy of hyperspectral image (HSI) in China is made up by HJ-1A satellite, which makes more study and application possible. But comparing with other HSI, low spatial resolution turns into a big limiting obstacle for application. In order to improve the HSI quality and make full use of the existing RS data, this paper proposed a fusion approach basing on 3D wavelet transform (3D WT) to fusing HJ-1A HSI and Multispectral image (MSI) using their 3D structure. Contrasting with the principal component transform (PCA) and Gram-Schmidt fusion approach, which are mature at present, 3D WT fusion approach use all bands of MSI to its advantage and the fusion result perform better in both spatial and spectral quality.

scholarly journals SHORT PERIOD CHANGE DETECTION OF SPERCHIOS LOWER DELTA AREA USING SPACE RADAR IMAGES

2018 ◽  
Vol 36 (2) ◽  
pp. 919 ◽  
Author(s):  
Em. Psomiadis ◽  
G. Migiros ◽  
Is. Parcharidis ◽  
S. Poulos
Keyword(s):  
Principal Component ◽  
Hydrological Regime ◽  
Period Change ◽  
Optical Data ◽  
Delta Area ◽  
Principal Component Transform ◽  
Radar Images ◽  
Short Period ◽  
Landsat 7 ◽  
Changing Patterns

Being highly dynamic by nature, due to their changing hydrological regime and to the encroachment of urbanization, industrialization and changing patterns in agriculture, reliable and timely information of coastal areas is a prerequisite for their effective management. The aim of this paper is to assess the use of ERS-2 SAR satellite data to detect short period changes in the case of the R. Sperchios coastal area that is located at the eastern part of the Maliakos Gulf (near the middle of the east coast of the Greek mainland). A Landsat 7 (ΕΤΜ+) image served as a reference for the interpretation of the ERS images. In order to highlight and detect the changes occurred in the study area two methods were applied. The first method is based on the creation of a Temporal Differentiate Image, consisted of the three ERS-2 images (Figure 1). The second method concerns the implementation of Principal Component Transform (PCT) on the three multitemporal scenes. The final images derived from the two different methods were compared and evaluated. Both methods didn't show any significant change along the coastline. PCT method illustrates more clearly the seasonal changes of crops in the lower delta area. Eventually, radar technology gave the opportunity to discriminate shallow areas, which does not appear in satellite optical data. Concurrently, the effect of wind direction was investigated.

scholarly journals CLASSIFICATION OF SATELLITE FUSED DATA FOR LAND USE MAPPING IN DEVELOPMENT PLAN

2011 ◽  
Vol 9 (2) ◽  
Author(s):  
Norzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mazlan Hashim
Keyword(s):  
Land Use ◽  
Principal Component ◽  
Kappa Statistic ◽  
Development Plan ◽  
Remotely Sensed Data ◽  
Data Set ◽  
Principal Component Transform ◽  
Fused Image ◽  
Fine Resolution

Land use mapping in development plan basically provides resources of information and important tool in decision making. In relation to this, fine resolution of recent satellite remotely sensed data have found wide applications in land use/land cover mapping. This study reports on work carried out for classification of fused image for land use mapping in detail scale for Local Plan. The LANDSATTM, SPOT Pan and IKONOS satellite were fused and examined using three data fusion techniques, namely Principal Component Transfonn (PCT), Wavelet Transform and Multiplicative fusing approach. The best fusion technique for three datasets was determined based on the assessment of class separabilities and visualizations evaluation of the selected subset of the fused datasets, respectively. Principal Component Transform has been found to be the best technique for fusing the three datasets, where the best fused data set was subjected to further classification for producing level of land use classes while level II and III pass on to nine classes of detail classification for local plan. The overall data classification accuracy of the best fused data set was 0.86 (kappa statistic). Final land use output from classified data was successfully generated in accordance to local plan land use mapping for development plan purposes.

scholarly journals Automatic Quantification of Immunohistochemically Stained Cell Nuclei Using Unsupervised Image Analysis

1998 ◽  
Vol 16 (1) ◽  
pp. 29-43 ◽  
Author(s):  
Petter Ranefall ◽  
Kenneth Wester ◽  
Ewert Bengtsson
Keyword(s):  
Principal Component ◽  
Cell Nuclei ◽  
Maximum Likelihood Classification ◽  
Automatic Quantification ◽  
Principal Component Transform ◽  
Independent Test ◽  
Principal Component Approach ◽  
Component Approach ◽  
Fully Automatic ◽  
Component Image

A method for quantification of images of immunohistochemically stained cell nuclei by computing area proportions is presented. The image is transformed by a principal component transform. The resulting first component image is used to segment the objects from the background using dynamic thresholding of theP2/A‐histogram, whereP2/Ais a global roundness measure. Then the image is transformed into principal component hue, defined as the angle around the first principal component. This image is used to segment positive and negative objects. The method is fully automatic and the principal component approach makes it robust with respect to illumination and focus settings. An independent test set consisting of images grabbed with different focus and illumination for each field of view was used to test the method, and the proposed method showed less variation than the intraoperator variation using supervised Maximum Likelihood classification.

Principal component transform — Outer product analysis in the PCA context

2008 ◽  
Vol 93 (1) ◽  
pp. 43-48 ◽  
Author(s):  
A.S. Barros ◽  
R. Pinto ◽  
D. Jouan-Rimbaud Bouveresse ◽  
D.N. Rutledge
Keyword(s):  
Principal Component ◽  
Product Analysis ◽  
Outer Product ◽  
Principal Component Transform
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