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De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

查看全文 作　　者：Rizwan [1]Sadiq;Muhammad Bilal [2]Qureshi;Muhammad Mohsin [3,4]Khan 高影响力作者 机构地区：[1]Dept.of Electrical and Electronic Engineering,Koc University,Istanbul,Turkey;[2]Dept.of Electrical and Computer Engineering,COMSATS University,Islamabad,Abbottabad Campus,Pakistan;[3]Dept.of Radiology and Biomedical Imaging,Yale University,CT,USA;[4]Sino-Pak Center for Artificial Intelligence(SPCAI),Pak-Austria Fachhochschule:Institute of Applied Sciences and Technology(PAF-IAST),Haripur,Pakistan高影响力机构 出　　处：《Chinese Journal of Electronics》索引2023年第32卷第1期,共11页高影响力期刊 摘　　要：Synthetic aperture radar(SAR) imaging is an efficient strategy which exploits the properties of microwaves to capture images.A major concern in SAR imaging is the reconstruction of image from back scattered signals in the presence of noise.The reflected signal consist of more noise than the target signal and it is a challenging problem to reduce the noise in the collected signal for better reconstruction of an image.Current studies mostly focus on filtering techniques for noise removal.This can result in an undesirable point spread function causing extreme smearing effect in the desired image.In order to handle this problem,a computational technique,particle swarm optimization(PSO) is used for de-noising purpose and later the target performance is further improved by an amalgamation of Wiener filter.Moreover,to improve the de-noising performance we have exploited the singular value decomposition based morphological filtering.To justify the proposed improvements we have simulated the proposed techniques and results are compared with the conventional existing models.The proposed method revealed considerable decrease in mean square error compared to Wiener filter and PSO techniques.Quantitative analysis of image restoration quality are also presented in comparison with Wiener filter and PSO based on the improvement in signal to noise ratio and peak signal to noise ratio. 关 键 词：Remote sensing Synthetic aperture radar imaging Wiener filter Particle swarm optimization
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