A Review:Image Fusion Techniques for Multisensor Images

Multisensor Images Fusion Based on Feature-Level

Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for...

A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

A Data Fusion Algorithm for Multisensor Systems

Data fusion techniques are used in many tracking and surveillance systems as well as in applications where reliability is of a main concern. One solution for design of such systems is to employ a number of sensors (maybe of different types) and to fuse the information obtained from all these sensors on a central processor. Past attempts to solve this problem required an organization of a feedba...

Multisensor Data Fusion

Multisensor Fusion and Integration

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview...