Enhanced Sensitivity of Motion Detection in Satellite Videos using Instant Learning Algorithms

Abstract

Satellite videos are drawing attention of the frontiers in the core of video image processing. Satellite videos are in common used for weather forecast. The satellite weather videos are analyzed for various parameters in prediction of weather. The motion detection in these videos plays a vital role in the prediction of weather. By using the existing methodologies in the video motion detection, only the edges are detected as moving area and the others are left as such. There lies a need for the proposed methodology to detect the multiple motion detection for getting the satellite video processed with even more sensitivity and fidelity. This paper justifies the use of the proposed methodology using iterated training algorithm in the processing of satellite video downloaded from the NASA videos.