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...

Satellite Images are used in many fields of research and enhancement of these images is a very important process. Satellite image enhancement is done using various transform techniques, filters and interpolation methods. This paper discusses a method of satellite image enhancement using Curvelet transform and interpolation technique. The quality of the enhanced image is measured using parameter...

The preparation of vegetation cover maps by used the land inventory and a traditional method has a lot of cost and time. But today, remote sensing is one of the main sources of data collection and information production for study and monitoring land resources, and was efficient tools for providing quickly and timely data and information needs for program planning in the natural resource filed. ...

Remote Sensing satellite image database which allows image portion retrievals utilizing principal component which consists of spectral and spatial features extracted from the imagery data is proposed. Through the experiments with actual remote sensing satellite images, it is found that the proposed image retrieval does work so well. Keywords—Image retrieval; Spectral and spatial features; e

This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is ...

Satellite scene classification is challenging because of the high variability inherent in satellite data. Although rapid progress in remote sensing techniques has been witnessed in recent years, the resolution of the available satellite images remains limited compared with the general images acquired using a common camera. On the other hand, a satellite image usually has a greater number of spe...

AbstractThe Researchers uses Satellite images for their Research work in many fields. The Satellite images have issues with their resolution. So, the images which loses their high frequency contents. And they appeared as blurred image. This paper proposes a resolution enhancement technique called Multi Wavelet Transform (MWT). This technique obtains the interpolation of high frequency sub bands...

Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they ...