measureNoise
使用Imatest测量噪声®eSFR图表
语法
噪音(图表)
描述
noiseTable= measureNoise (图表）
例子
测量eSFR图的噪声
这个例子展示了如何在eSFR图表上测量灰色补丁roi的噪声。
将eSFR图表的图像读入工作区。线性化图像。
I = imread(“eSFRTestImage.jpg”）;I = rgb2lin(I);
创建一个esfrChart对象，然后显示带有ROI注释的图表。20个灰色补丁roi用红色数字标注。
图表= esfrChart(I_lin);displayChart(图);
测量所有灰斑roi中的噪声。
噪音(图表)
noiseTable =20×22表ROI MeanIntensity_R MeanIntensity_G MeanIntensity_B RMSNoise_R RMSNoise_G RMSNoise_B PercentNoise_R PercentNoise_G PercentNoise_B SignalToNoiseRatio_R SignalToNoiseRatio_G SignalToNoiseRatio_B SNR_R SNR_G SNR_B PSNR_R PSNR_G PSNR_B RMSNoise_Y RMSNoise_Cb RMSNoise_Cr ___ _______________ _______________ _______________ __________ __________ __________ ______________ ______________ ______________ ____________________ ____________________ ____________________ ______ ______ ______ ______ ____________ __________ ___________ ___________ 1 0.85545 0.99547 1.0086 0.35301 0.083743 0.14715 0.13843 0.03284 0.057704 2.4233 11.887 6.8544 7.6881 2 0.87232 0.98453 0.97984 0.33469 0.14975 0.1523 0.13125 0.058724 0.059725 2.6064 6.5746 6.4337 8.3207 16.357 16.169 57.638 64.477 0.13565 00 3 1.0372 1.116 1.1516 0.22956 0.3202 0.36169 0.090022 0.12557 0.14184 3.4852 3.1839 13.099 10.845 10.059 60.913 58.022 56.964 0.181620.072854 0.072854 4 1.9059 2.0097 0.1174 0.3517 0.22062 0.37649 0.086516 0.14764 5.4192 9.1095 0.087836 0.087836 5 3.1203 4.0434 5.0116 0.5796 0.65321 1.0583 0.25616 6.1901 4.7357 14.621 15.834 13.508 52.868 51.83 47.639 0.59331 0.54593 0.50555 6 4.2193 5.4594 7.4619 0.7302 0.75399 1.0733 0.28635 0.29568 0.42091 5.7782 7.24023 15.236 17.196 16.843 50.862 50.584 47.516 0.69911 0.2886 0.30988 7.376 10.89215.463 1.0547 1.274 1.6981 0.41362 0.4996 0.66592 9.1059 17.998 18.639 19.186 47.668 46.028 43.532 1.0662 0.5369 0.5082 8 12.274 15.69 20.872 1.3671 1.4261 1.7696 0.53613 0.55927 0.69394 8.9777 11.002 11.795 19.063 20.829 21.434 45.415 45.048 43.174 1.2247 0.45011 0.55314 9 18.901 22.701 30.388 1.5886 1.6768 2.3076 0.2298 0.65757 0.90494 11.898 13.538 0.5006 10 25.215 31.376 40.889 1.4167 0.57663 0.5649 0.74115 0.754851.0058 13.342 16.3 16.722 22.504 24.244 24.466 42.602 42.443 39.95 1.5838 0.62542 0.61931 11 37.672 45.462 59.961 2.5106 2.5421 1.2867 15.005 17.8453 0.99689 1.2867 17.005 17.825 25.049 25.237 40.135 40.027 37.81 2.1486 0.74816 0.59645 12 51.662 58.975 73.656 2.9606 3.047 3.7934 1.161 1.1949 1.4876 17.45 19.355 19.417 24.836 25.736 25.764 38.703 38.453 36.55 3.5243 0.93749 0.75463 13 70.636 3.9746 1.2127 1.2014 1.5587 22.834 25.168 24.007 27.172 28.017 27.60738.325 38.406 36.145 2.6906 0.83735 0.61102 14 85.824 97.029 113.7 3.9206 3.4895 3.8203 1.3684 1.4982 21.89 27.806 29.763 26.805 28.883 29.474 36.264 37.276 36.489 2.9718 0.60018 1.323 136.45 4.0307 3.7118 4.163 1.4556 1.6325 28.267 33.167 32.776 29.026 30.414 30.311 36.023 36.739 35.743 3.1531 142.32 153.02 3.5568 3.4969 1.7145 38.604 40.7 35 31.733 32.192 30.881 37.11 37.257 35.317 2.8509 1.5228 0.93134
显示在20个灰色斑块roi上的三个颜色通道的平均原始信号和信噪比(SNR)的图形。
图subplot(1,2,1) plot(noiseTable.)ROI, noiseTable。MeanIntensity_R,“r-o”，.．.noiseTable。投资回报率,noiseTable。MeanIntensity_G,“g-o”, noiseTable。投资回报率,.．.noiseTable。MeanIntensity_B,“这”)标题(“信号”) ylabel (“强度”)包含(“灰色ROI数”网格)在次要情节(1、2、2)情节(noiseTable。ROI, noiseTable。SNR_R,的r - ^, noiseTable。投资回报率,.．.noiseTable。SNR_G,“g - ^”, noiseTable。投资回报率,noiseTable。SNR_B,“b - ^”)标题(“信噪比”) ylabel (“数据库”)包含(“灰色ROI数”网格)在
输入参数
输出参数
提示
对线性化数据进行噪声测量。使用
rgb2lin线性化sRGB图像。
在R2017b中引入
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