The most significant problem may be undesirable effects for the spectral signatures of fused images as well as the benefits of using fused images mostly compared to their source images were acquired at the same time by one sensor. They may or may not be suitable for the fusion of other images. It becomes therefore increasingly important to investigate techniques that allow multi-sensor, multi-d...

CFNN hybrid system in Multi-sensor data fusion introduced fuzzy logic reasoning and neural network adaptive, self-learning ability, and using fuzzy neurons, so networking skills appropriate to adjust the input and output fuzzy membership function, and can dynamically optimize fuzzy reasoning in global by means of compensated logic algorithm, to make the network more fault tolerance, stability a...

Understanding mechanisms of materials deterioration during service life is fundamental for their confident use in the building sector. This work presents analysis time series data related to wood weathering acquired at three scales (molecular, microscopic, macroscopic) with different sensors. By using several complementary techniques, material description precise and complete; however, provided...

We present the general idea of a computer vision structure-from-motion framework that makes use of sensor fusion to provide very accurate and efficient multi-view reconstruction results that can capture internal geometry. Given the increased ubiquity and cost-effectiveness of embedding sensors, such as positional sensors, into objects, it has become feasible to fuse such sensor data and camera-...

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle’s position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satell...

Distributed sensor networks are a significant technology nowadays. Inexpensive, smart devices with multiple sensors provide opportunities for instrumenting, monitoring and controlling targeting systems. Such sensor nodes have capability for acquiring and embeddedprocessing of variety of data forms. Collaborative signal processing and fusion algorithms are needed to aggregate the distributed dat...

Sensor data have broadened their scope recently, ranging now from the simple time series measurements to, e.g., hyperspectral satellite image maps timeseries. In addition to observed data, simulation data increasingly have to be merged, for example 4-D ocean and atmospheric data. The majority of these data fall into the category of multi-dimensional rasters. However, when it comes to flexible r...