SAR Electromagnetic Image Conditioning Using a New Adaptive Particle Swarm Optimization
B. Malakonda Reddy, Md. Zıa Ur Rahman · The Applied Computational Electromagnetics Society Journal (ACES) · 2018
In Synthetic Aperture Radar (SAR) image Objects or region detection is a difficult task because of improper variation of boundary due to speckle noise. So, it creates the problems of human being for the analysis. In fact, this process leads to inaccurate in the detection and measurement of object parameters. In this paper proposes a new automatic detection of objects from SAR images. For detection of objects an effective method is introduced using the variance of Particle Swarm Optimization (PSO) called Adaptive PSO (APSO). In this paper develops the dynamically varying the inertia weight for PSO and tuning the social components, cognitive components. This APSO find the optimal threshold value for making the better segmentation by preprocessing SAR image with effective Filter. The proposed APSO method has also compared with existing methods in terms of detection of object regions and parameter calculations.