Human Activity Registration Using Multisensor Data Fusion

Multisensor data fusion using fuzzy concepts

In this study, a fuzzy-based multisensor data fusion classifier is developed and applied to land cover classification using ERS-1/JERS-1 SAR composites. This classifier aims at the integration of multisensor and contextual information in a single and a homogeneous framework. Initial Fuzzy Membership Maps (FMM) to different thematic classes are first calculated using classes and sensors a priori...

Multisensor Data Fusion

Classification Accuracy Increase Using Multisensor Data Fusion

The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use o...

Multisensor Data Fusion Using Multiresolusion Analysis (mra)

The objective of this study is to propose multiresolution data fusion scheme using multiresolution analysis (MRA). Three techniques compared, respectively based on Haar wavelet basis (HWB), Daubechies wavelet basis (DWB), and IHS transform. Daubechies Wavelet Basis (DWB) is far more efficient than the HWB and IHS transform, thus establishing the advantages for data fusion of formally multiresol...

Multisensor Data Fusion

IMultisensor data fusion refers to the acquisition, processing and synergistic combination of information gathered by various knowledge sources and sensors to provide a better understanding of a phenomenon. It is a fascinating and rapidly evolving field that has generated a lot of excitement in the research and development community. These concepts are being applied to a wide variety of fields ...