Volume 18, No. 2, 2021

Extended Distributed Framework for Feature Extraction in Remote Sensing Imagery with High Resolution


T. Naga Raju and Dr. Chittineni Suneetha

Abstract

Remote Sensing imagery is used vastly in the areas of human activities investigation, environmental changes monitoring and geo-spatial data updation in a rapidly increasing way. Humans can easily and appropriately interpret the normally shot pictures but this is a difficult task for the computer to automatically interpret information from the given images. One of the prominent phases is in finding the way to extract the projected information from the given imagery and its conversion to wrath-ful data which can be used for further research. The motto is the generation of an algorithm which aims to be very efficient during of processing of huge images that include enhancement of efficiency in processing, correlation finding amongst given data and extraction of continuous features. In order to accomplish all these purposes as stated above, we hereby put forward an algorithm Extended Feature Extraction and Detection in High Resolution Remote Sensing (HRRS) Imagery to detect rivers. The proposed system is established with Hadoop Distributed Framework in order to enhance the efficiency of total system.


Pages: 1035-1046

DOI: 10.14704/WEB/V18I2/WEB18372

Keywords: Feature Extraction, Image Processing, Remote Sensing.

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