this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

Destructive wildfires are becoming an annual event, similar to climate change, resulting in catastrophes that wreak havoc on both humans and the environment. The result, however, is disastrous, causing irreversible damage ecosystem. location of incident hotspot can sometimes have impact early fire detection systems. With advancement intelligent sensor-based control technologies, multi-sensor da...

Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multisensor/multispectral images has become a very important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity o...

A multisensor feature-based fusion approach to target recognition using a framework of model-theory is proposed. The Best Discrimination Basis Algorithm (BDBA) based on the best basis selection technique and the Sensory Data Fusion System (SDFS) based on logical models and theories are applied for feature extraction. The BDBA selects the most discriminant basis. The SDFS rst selects features, w...

Remote sensing delivers multimodal and –temporal data from the Earth’s surface. In order to cope with these multidimensional data sources and to make the most of them, image fusion is a valuable tool. It has developed over the past few decades into a usable image processing technique for extracting information of higher quality and reliability. As more sensors and advanced image fusion techniqu...