计算技术与自动化Issue(3)：92-96,5.
一种对Gamma分布的SAR图像相干斑去噪方法
A Denoising Method Aiming at the Speckle of Gamma Distribution SAR Image
摘要
Abstract
After processing by logarithmic transformation,the Gamma distribution speckle of SAR images are analogous to Gasussian distribution.In view of this,a BP neural network restoration denoising method based on particle swarm optimi-zation is proposed.Firstly,noiseless images are process by Gasussian noise.then,the result image and the noiseless images are made training pair,which is used in training the optimizational BP neural network.Lastly,using the BP neural network to restore SAR Images for the purpose of removing speckle.The experiment shows,compared with traditional denoising algo-rithm,the method can effectively solve the problem of image distortion and edge burring,have fast convergence rate and less iterations,is better in normalized mean square error (NMSE)and peak signal-to-noise ratio (PSNR).关键词
BP神经网络/粒子群优化/合成孔径雷达图像/去噪Key words
BP neural network/particle swarm optimization/SAR image/denoising分类
信息技术与安全科学引用本文复制引用
宋发兴,杨献超,郭健,高留洋,刘东升..一种对Gamma分布的SAR图像相干斑去噪方法[J].计算技术与自动化,2014,(3):92-96,5.基金项目
国防十二五预研基金项目(40405070102) （40405070102）
