With the aim of automatically extracting fine change information from ground objects, detection (CD) for very high resolution (VHR) remote sensing images is extremely essential in various applications. However, increase spatial resolution, more complicated interactive relationships evident diversity spectra, and severe speckle noise make accurately identifying relevant changes challenging. To a...

It is often useful to know the positions of nodes in a network. However, in a large network it is impractical to build a single global map. In this paper, we present a new approach for distributed localization called Positioning using Local Maps (PLM). Given a path between a starting node and a remote node we wish to localize, the nodes along the path each compute a map of their local neighborh...

We are presenting in this volume selected, peer-reviewed, short papers that were presented at the 3rd International Conference on Variable Neighborhood Search (VNS’14) which took place in Djerba, Tunisia, during October 8-11, 2014.

Available online 31 July 2008

The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefo...

Mangroves are valuable contributors to coastal ecosystems, and remote sensing is an indispensable way to obtain knowledge of the dynamics of mangrove ecosystems. Due to the similar spectral features between mangroves and other land cover types, challenges are posed since the accuracy is sometimes unsatisfactory in distinguishing mangroves from other land cover types with traditional classificat...

This paper presents an automatic context-sensitive technique robust to registration noise (RN) for change detection (CD) in multitemporal very high geometrical resolution (VHR) remote-sensing images. Exploiting the properties of RN in VHR images, the proposed technique analyzes the distribution of the spectral change vectors (SCVs) computed according to the change vector analysis in an adaptive...

In this paper wk have used two fuzzy clustering algorithms, namely Fuzzy C-Means (FCM) and Gustafson Kessel Clustering (GKC) for unsupervised change detection in multitemporal remote sensing images. In conventional FCM & GKC no spatio-contextual information is taken into account and thus the result is not so much robust to noise/outliers. By incorporation of local neighborhood informationthe pe...