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师瑛杰

于 2020-06-20 发布 文件大小:13631KB
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下载积分: 1 下载次数: 1

代码说明:

  解决散斑图像的重建问题,主要是使用了相位恢复算法(to study the picture problem)

文件列表:

HIO1.png, 143650 , 2019-07-17
HIO2.png, 221470 , 2019-07-17
HIO3.png, 183150 , 2019-07-17
HIO_ER, 0 , 2019-07-17
HIO_ER\1.bmp, 287446 , 2019-05-20
HIO_ER\centerImg.m, 283 , 2017-04-05
HIO_ER\Constrain.m, 315 , 2017-04-05
HIO_ER\ER.m, 598 , 2019-01-15
HIO_ER\fftXcorr2.m, 622 , 2019-04-29
HIO_ER\HIO.m, 851 , 2019-03-06
HIO_ER\PhaseRetrieval.m, 1597 , 2019-07-17
HIO_ER\PhaseRetrieval为主函数.txt, 0 , 2019-07-17
ParticleSwarmOptimization-master, 0 , 2019-07-17
ParticleSwarmOptimization-master\.gitignore, 42 , 2016-03-20
ParticleSwarmOptimization-master\fftXcorr2.m, 622 , 2019-04-29
ParticleSwarmOptimization-master\GoldsteinPrice.m, 614 , 2016-03-20
ParticleSwarmOptimization-master\Himmelblau.m, 635 , 2016-03-20
ParticleSwarmOptimization-master\license.txt, 1082 , 2016-03-20
ParticleSwarmOptimization-master\makeStruct.m, 531 , 2016-03-20
ParticleSwarmOptimization-master\mergeOptions.m, 2383 , 2016-03-20
ParticleSwarmOptimization-master\plotBowl.m, 1723 , 2016-03-20
ParticleSwarmOptimization-master\plotGoldsteinPrice.m, 2814 , 2016-03-20
ParticleSwarmOptimization-master\plotHimmelblau.m, 3614 , 2016-03-20
ParticleSwarmOptimization-master\plotPsoHistory.m, 2087 , 2016-03-20
ParticleSwarmOptimization-master\plotStyblinskiTang.m, 2825 , 2016-03-20
ParticleSwarmOptimization-master\PSO.m, 14007 , 2019-07-17
ParticleSwarmOptimization-master\PSO_Image.png, 144306 , 2016-03-20
ParticleSwarmOptimization-master\README.md, 6066 , 2016-03-20
ParticleSwarmOptimization-master\StyblinskiTang.m, 460 , 2016-03-20
ParticleSwarmOptimization-master\StyblinskiTangNoise.m, 551 , 2016-03-20
ParticleSwarmOptimization-master\test.m, 832 , 2019-07-17
ParticleSwarmOptimization-master\TEST_PSO_1.m, 767 , 2016-03-20
ParticleSwarmOptimization-master\TEST_PSO_2.m, 937 , 2016-03-20
ParticleSwarmOptimization-master\TEST_PSO_3.m, 946 , 2019-06-24
ParticleSwarmOptimization-master\TEST_PSO_4.m, 821 , 2016-03-20
ParticleSwarmOptimization-master\TEST_PSO_5.m, 1028 , 2016-03-20
ParticleSwarmOptimization-master\TEST_PSO_6.m, 4011 , 2016-03-20
ParticleSwarmOptimization-master\TEST_PSO_7.m, 1088 , 2016-03-20
ParticleSwarmOptimization-master\测试目标, 0 , 2019-07-17
ParticleSwarmOptimization-master\测试目标\2.tiff, 2313746 , 2019-07-08
ParticleSwarmOptimization-master\测试目标\三孔原图.tiff, 2313746 , 2019-07-08
ParticleSwarmOptimization-master\测试目标\光斑大小.tiff, 2313746 , 2019-07-08
基于光学记忆效应的非侵入式散射成像方法研究_吴腾飞.caj, 12493083 , 2019-07-17
待测试的2个数据集.txt, 244 , 2019-07-17

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    说明:  有数字1和2的图片各四十张,利用mat lab读取图片并将其二值化,得到只由0和1表示的矩阵,根据数字的不同特征,选择两个特征值,用来对分类器进行训练,最后用剩下的5个1和5个2来进行测试,看分类器是否可以正确的对数据进行分类。(Figures 1 and 2 pictures of the 40, using mat lab picture and secondly, the value of reading, and received only by 0 and 1, said matrix, according to the number of different features, select the two characteristic values, used to classifier training, and finally with the remaining 5 1 and 5 2 to carry out tests to see whether the classifier can correctly classify the data.)
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    积分:1
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    自己用MATLAB写的一个基于多项式插值的亚像素处理算法,处理速度快(sub-pixel edge detect)
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