Introduction Outcomes attributable to the research funded through the 2005 NCPPT grant can be summarized as follows: 1) Protocols for the detection of archaeological sites through the analysis of commercially available synthetic aperture radar (SAR) and multispectral images. Previously existing protocols for site detection through image analysis had utilized images generated from synthetic aper...

The Egnatia highway, a modern closed motorway 670 kilometres long, is one of the largest road construction projects in Europe, running across Northern Greece. In order to record and analyze the spatial and environmental effects that inevitably the Egnatia highway has caused to its surroundings, the need for effective and efficient integration of land cover dynamic information is becoming more a...

From the birth of multi-spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray-scale images, instead of an ensemble of an n-D realization. However, it has been proved that using vector-based tools leads to a more appropriate understanding of color images and thus more efficient algorithms for processing them. Such tools are...

Remotely sensed multitemporal, multisensor data are often required for change detection applications. A common problem associated with the use of these data is the grey value difference caused by non-surface factors such as different illumination, atmospheric, or sensor conditions. Such a difference makes it difficult to accurately detect changes using automatic methods. Effective image normali...

In this paper we present an automated method for classifying astronomical objects in multispectral wide-field images. The method is divided into three main tasks. The first one consists of locating and matching the objects in the multispectral images. In the second task we create a new representation for each astronomical object using its multispectral images, and also we find a set of features...

The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-p...

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware datadriven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical ...

Multispectral images are composed of a series of images at differing optical wavelengths. Since these images can be quite large, they invite efficient source coding schemes for reducing storage and transmission requirements. Because multispectral images include a third (spectral) dimension with nonstationary behavior, these multilayer data sets require specialized coding techniques. The authors...

We investigated the Classification of satellite images and multispectral remote sensing data .we focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area and green area. We carried out classification in three modules namely (a) Preprocess...

Giant Salvinia (Salvinia molesta) is one of the world’s most invasive aquatic weeds. We evaluated the accuracy of airborne multispectral digital video imagery for separating giant salvinia from other aquatic and terrestrial features at a study site located in northeast, Texas. The five-band multispectral digital video imagery was subjected to an unsupervised computer analysis to derive a themat...