Multi-spectral images classification based on intelligent water drops algorithm

Almas Ahmed Khaleel


Mosul's city land covers Soil, Cultivated Land, Stony, Pastoral Land, Water, and Ploughed Agricultural Land. We have classified multispectral images captured by the sensor (TM) carried on the Landsat satellite. Integrated Approach of Intelligent Water Drops algorithm is used to identify natural terrain. In this research, IWDs have been suggested to find the best results for multispectral image classification. The purpose of using an algorithm, give accurate and fast results by comparing the IWD algorithm with the K-mean algorithm. The IWD algorithm is programmed using the Matlab2017b software environment to demonstrate the proposed methodology's effectiveness. The proposed integrated concept has been applied to satellite images of Mosul city in Iraq. By comparing the IWD with the K-mean, we found clear time superiority of the IWD algorithm, equal 1.4122 with (k-mean) time equal 18.9475. Furthermore, the water drop algorithm's classification accuracy is 95%, while the K-Mean classification accuracy is 83.3%. Based on the results and analysis, we conclude that the IWD is a promising and robust approach to detecting remote sensing image changes and multispectral image classification.


Digital image processing; Image classification; Mosul map; Remote sensing; Swarm intelligence;



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