Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a comp...

With improved spatial resolution of available satellite images and the ability to collect the stereo images within a short time period, the importance of satellite images for generating elevation information has grown. Most of the users try to use satellite images because of the reasonable time and cost for ordering. The speed of information generation by satellite sensors from planning to exec...

From the immense amount of images being sent to Earth by satellites, it takes too much time for a human to go through each image and classify what the image represents. Therefore, we are able to use classifiers to classify these images. In this paper, we used two different classification methods to classify satellite images. Between the two classifiers we used, both K-Nearest-Neighbor and Suppo...

Because the cartography is often deficient, the use of satellite images is the best way to know the land use of Africa. But to extract a reliable map from these raw data is not an easy task. The aim of this study was to find a method to map the main landscape units, a method which can be easily reproducible. Satellite images were chosen according to the agricultural calendar, among those freely...

Discrimination between texture edges and geometrical edges is very difficult in low contrast images. Satellite images are low contrast images. It is important to extract the edges that are not clearly visible in case of Satellite images. The present work encompasses a new edge detection algorithm using newly constructed differentiator. Chebyshev polynomial based fractional order differentiator ...

This study proposes a novel tiling approach to capture an image of an entire object. Multi-spectral and multi-temporal satellite images are obtained a priori, and these individual image pieces can then be joined together at a later date to form an image of the entire object. The effectiveness of the proposed technique has been studied by tiling partially overlapping satellite mosaic images of t...

in recent years, acquiring information of remote sensing data, especially satellite data has excessively increased and several methods are presented in order to improve the quality of remote sensing studies in earth sciences. it is possible to manage many projects and provide different types of thematic maps in a short period of time, and a low cost by utilizing satellite data and gis method. r...

This article presents a new methodology for detecting road network and planning the path for vehicle motion using road map and satellite/aerial images. The method estimates road regions from based on network models, which are created from road maps and satellite images on the basis of using image-processing techniques such color filters, difference of Gaussian, and Radon transform. In the case ...

In this paper we propose a supervised learning system for counting and localizing palm trees in high-resolution, panchromatic satellite imagery (40cm/pixel to 1.5m/pixel). A convolutional neural network classifier trained on a set of palm and no-palm images is applied across a satellite image scene in a sliding window fashion. The resultant confidence map is smoothed with a uniform filter. A no...