adaptive modeling on satellite image processing and info extraction using knowledge fusion mining

R.Dhivya Bharathi,C.Sundhar

Published in International Journal of Advanced Research in Electronics, Communication & Instrumentation Engineering and Development

ISSN: 2347 -7210          Impact Factor:1.9         Volume:2         Issue:1         Year: 05 April,2016         Pages:51-60

International Journal of Advanced Research in Electronics, Communication & Instrumentation Engineering and Development

Abstract

Satellite Imagery is the most advent of landscape analysis. These satellite images were made from the physical point of element in a raster image called pixels.In existing system, a system has been designed to analyze the changes acquired in a particular landscape by utilizing satellite imagery of the landscape. This system formulates a Comparative analysis with historical and the recent imagery of the landscape with respect to the changes in the soil, water, weather, landscape. The proposed system designs a system that formulates a comparative analysis with historical and the recent imagery by incorporating the concept of simage replacement. The resultant of the existing methodology does not predict or suggest anything for the future about the landscape whereas the proposed methodology does it with by means of image replacement. The satellite imagery under subject is tuned up with its part with a minute changes in the picture with a vision to the future and the comparative analysis has been made. Performance analysis has been done to the comparative analysis system with respect to the time and visualized graphically.

Kewords

satellite images and modies images

Reference

1.Tomasz F. Stepinski, Pawel Netzel, and Jaroslaw Jasiewicz,‘LandEx A GeoWeb Tool for Query and Retrieval ofSpatial Patterns in Land Cover Datasets”, IEEE journal of selected topics in applied earth observations and remote sensing, Vol.7, no. 1, January 2014. 2. R. Datta, D. Joshi, J. Li, and J. Z.Wang, “Image retrieval: Ideas, influences, and trends of the new age,” ACM Computing Surveys, vol. 40,pp. 1,60, 2008. 3. M. Lew, N. Sebe, C. Lifi, and R. Jain, “Content based multimedia information retrieval State of the art and challenges,” ACM Trans. Multimedia Comput., Commun., Appl., vol. 2, no. 1, pp. 1,19, 2006.