Abstract
TheProposed architectonics comprises threemain units, such as Remote Sensing Big Data Acquisition Unit (RSDU), Data Processing Unit (DPU) and Data Analysis Decision Unit (DADU). First, RSDU acquires datafrom the satellite and dispatchesacquired data to the Base Station, where initial process takes place. Second, DPU plays a vital role in architecture, for efficient processing of real-time Big Data by providing filtration, load balancing, and parallel processing. Finally, DADU is the uppermosttier of the proposed scheme, which is responsible for compilation, storage of the outcome, and reproduction of decision upon the outcome received from DPU. Thus, it results in analyzing the actual time, for remote sensing Big Data using globe observatory system. Furthermore, the proficiency of storing incoming data to implement offline analysis on largely stored dumps, when required. Eventually, a detailed analysis of remotely sensed globe observatory Big Data for land and sea area are provided using hadoop and Canny edge detection algorithmwhich uses a multi-stage algorithm to detect wide range of edges in images.
Keywords
Remote Sensing Big Data Acquisition Unit (RSDU)
Data Processing Unit (DPU)
Data Analysis Decision Unit (DADU)
Big data
Hadoop
Canny edge detection algorithm.
Authors
How to Cite this Article
K. Akshaya, K.Gangatharan, R.Vishnu Priya, N. Suresh Kumar (2016).
"ENHANCING THE PERFORMANCE OF FILTERING USING CANNY EDGE DETECTION ALGORITHM FOR REAL TIME BIG DATA WITH HADOOP".
International Journal of Contemporary Research in Computer Science and Technology,
2(3), pp. 636-640.
