RS data fusion by local mean and variance matching algorithms: their respective efficiency in a complex urban context

IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482) ◽

10.1109/dfua.2001.985736 ◽

2002 ◽

Cited By ~ 6

Author(s):

Y. Cornet ◽

S. de Bethune ◽

M. Binard ◽

F. Muller ◽

G. Legros ◽

...

Keyword(s):

Data Fusion ◽

Urban Context ◽

Mean And Variance ◽

Local Mean

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Based on Local Mean and Variance of Adaptive Pulse Coupled Neural Network Image Fusion

2011 International Conference on Multimedia and Signal Processing ◽

10.1109/cmsp.2011.125 ◽

2011 ◽

Cited By ~ 1

Author(s):

Jianfeng Li ◽

Beiji Zou ◽

Yixiong Liang ◽

Goujiang Xin

Keyword(s):

Neural Network ◽

Image Fusion ◽

Pulse Coupled Neural Network ◽

Mean And Variance ◽

Local Mean

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Study on Multisensor Data Fusion of Ultrasonic Sensor

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.722.44 ◽

2013 ◽

Vol 722 ◽

pp. 44-48

Author(s):

Bao Jun Liu

Keyword(s):

Embedded Systems ◽

Data Fusion ◽

Fuzzy Set ◽

Measured Data ◽

Fusion Method ◽

Multisensor Data Fusion ◽

Mean And Variance ◽

Outlier Data ◽

Final Expression ◽

Multisensor Data

Aiming at data fusion of Autonomous car multisensors experiment at many times on distances, a novel fusion method is proposed based on the approach degree and weights. The method calculate mean and variance based on the measured sensors data, Using the maximum and minimum approach degree of this fuzzy set , the approach degree of the measured data from various sensors is processed quantitatively ,eliminating outlier data by Grubbs method, assigned the weights of data measured in the fusion process reasonably , so that the final expression of the data fusion is obtained, thus the data fusion of multisensor is realized.Test results demonstrate that this method can bring higher fusion precision, and more suitable for microcontroller and embedded systems applications.

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Change detection in urban context with multitemporal ERS-SAR images by using data fusion approach

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477) ◽

10.1109/igarss.2003.1294883 ◽

2004 ◽

Cited By ~ 4

Author(s):

V.P. Onana ◽

E. Trouve ◽

G. Mauris ◽

J.P. Rudant ◽

P.L. Frison

Keyword(s):

Data Fusion ◽

Change Detection ◽

Urban Context ◽

Sar Images ◽

Using Data ◽

Fusion Approach

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A local mean and variance active contour model for biomedical image segmentation

Journal of Computational Science ◽

10.1016/j.jocs.2019.03.003 ◽

2019 ◽

Vol 33 ◽

pp. 11-19 ◽

Cited By ~ 10

Author(s):

Yali Peng ◽

Shigang Liu ◽

Yongqian Qiang ◽

XiaoJun Wu ◽

Ling Hong

Keyword(s):

Image Segmentation ◽

Active Contour ◽

Active Contour Model ◽

Biomedical Image ◽

Contour Model ◽

Mean And Variance ◽

Local Mean

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AMELIORATING THE SPATIAL RESOLUTION OF HYPERION HYPERSPECTRAL DATA. THE CASE OF ANTIPAROS ISLAND

Bulletin of the Geological Society of Greece ◽

10.12681/bgsg.11337 ◽

2017 ◽

Vol 43 (3) ◽

pp. 1627

Author(s):

K. Nikolakopoulos ◽

Ev. Gioti ◽

G. Skianis ◽

D. Vaiopoulos

Keyword(s):

Spatial Resolution ◽

Aegean Sea ◽

Hyperspectral Data ◽

Pass Filter ◽

Multispectral Data ◽

High Pass Filter ◽

Mean And Variance ◽

Local Mean ◽

The Common ◽

High Pass

In this study seven fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. The panchromatic data have a spatial resolution of 10m while the hyperspectral data have a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data. The study area is Antiparos Island in the Aegean Sea.

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