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  Published Paper Details:

  Paper Title

CONTENT BASED SATELLITE CLOUD IMAGE RETRIEVAL AND RAINFALL ESTIMATION

  Authors

  D.CHANDRAPRAKASH

  Keywords

semantic gap, typhoons, hurricanes, aquatic, retrieval

  Abstract


In the last decade we witnessed a large increase in data generated by earth observing satellites. But today Satellite Image Retrieval is a big issue to discuss. There is huge amount of research work focusing on the retrieving of images in the image database. One of the most important steps in earlier stages of satellite image processing is cloud detection. Therefore, the satellite cloud images provide a valuable source of information in weather forecasting and early prediction of different atmospheric disturbances such as typhoons, hurricanes and also in the estimation of rainfall. Rainfall is the primary source for water. Rainfall forecasting is important for agriculture and living things. The type of rainfall is predicted by analyzing the size and shape of the cloud images. Shape is important feature in the meteorological satellite images. Different types of clouds have different shapes. The content based image retrieval with the fast and high matching retrieving ability is the need of the day for shape mining. The ultimate focus of this project reports to develop a Content Based Image Processing and Information as well as image retrieval (CBIPR) system using shape feature , for the retrieval of the satellite cloud images and also to forecast the rainfall from the meteorological satellite archival that allows us to study the past weather system and understand the current weather system.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTNCES049

  Paper ID - 180497

  Page Number(s) - 315-321

  Pubished in - Volume 6 | Issue 1 | December - 2017

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  D.CHANDRAPRAKASH,   "CONTENT BASED SATELLITE CLOUD IMAGE RETRIEVAL AND RAINFALL ESTIMATION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.6, Issue 1, pp.315-321, December - 2017, Available at :http://www.ijcrt.org/papers/IJCRTNCES049.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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