measureNoise
Measure noise of test chart
Description
esfrChart
Object
Use an esfrChart
object when you want to automatically detect
gray regions of interest (ROIs). The esfrChart
object supports the
Enhanced or Extended version of the Imatest® eSFR test chart [1].
measures the noise levels using the gray ROIs of an Imatest eSFR chart.noiseValues
= measureNoise(chart
)
Test Chart Image (since R2024a)
Use a test chart image for other types of test charts that are not supported by
the esfrChart
object. You must identify the positions of the
ROIs.
measures the noise in ROIs at positions noiseValues
= measureNoise(im
,roiPositions
)roiPositions
for
test chart image im
.
Examples
Measure Noise of eSFR Chart
Read an image of an eSFR chart into the workspace.
I = imread("eSFRTestImage.jpg");
Create an esfrChart
object, then display the chart with ROI annotations. The 20 gray patch ROIs are labeled with red numbers.
chart = esfrChart(I);
displayChart(chart,displayColorROIs=false, ...
displayEdgeROIs=false,displayRegistrationPoints=false)
Measure the noise in all gray patch ROIs.
noiseTable = measureNoise(chart)
noiseTable=20×22 table
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 9.4147 11.349 11.099 2.6335 1.9417 2.3106 1.0328 0.76145 0.90613 3.5749 5.8448 4.8036 11.065 15.335 13.631 39.72 42.367 40.856 1.6708 0.53508 1.0745
2 9.2873 10.896 10.503 2.405 2.1309 2.0966 0.94312 0.83564 0.82218 3.8617 5.1132 5.0099 11.736 14.174 13.996 40.509 41.56 41.701 1.736 0.26598 0.97869
3 13.488 14.95 15.017 2.4966 2.1156 2.5593 0.97907 0.82964 1.0036 5.4027 7.0668 5.8676 14.652 16.984 15.369 40.184 41.622 39.968 1.7942 0.73421 1.053
4 20.411 21.689 22.946 2.4395 2.0206 2.5556 0.95668 0.79241 1.0022 8.3666 10.734 8.9791 18.451 20.615 19.065 40.385 42.021 39.981 1.7945 0.68449 0.84796
5 29.189 34.144 38.442 3.0436 2.8317 4.1125 1.1936 1.1105 1.6127 9.5903 12.058 9.3476 19.637 21.625 19.414 38.463 39.09 35.849 2.304 1.3083 1.1864
6 35.009 40.337 47.544 3.2201 2.7705 3.6994 1.2628 1.0865 1.4508 10.872 14.56 12.852 20.726 23.263 22.179 37.973 39.28 36.768 2.3869 1.2887 1.1016
7 50.768 58.206 69.539 3.3931 3.2661 3.734 1.3306 1.2808 1.4643 14.962 17.821 18.623 23.5 25.019 25.401 37.519 37.85 36.687 2.7733 0.95879 0.7594
8 61.871 69.98 80.779 3.4734 3.0966 3.1214 1.3621 1.2144 1.2241 17.813 22.599 25.879 25.015 27.082 28.259 37.316 38.313 38.244 2.5957 0.54197 1.0178
9 77.115 83.999 96.869 3.1467 2.9973 3.5088 1.234 1.1754 1.376 24.507 28.025 27.607 27.786 28.951 28.821 38.174 38.596 37.228 2.5474 0.88964 0.86929
10 88.552 98.426 113.87 3.1846 2.8538 3.1835 1.2488 1.1191 1.2484 27.807 34.49 35.767 28.883 30.754 31.07 38.07 39.022 38.073 2.4073 0.66975 0.84965
11 107.25 116.97 132.94 3.3128 3.0561 3.2921 1.2991 1.1985 1.291 32.374 38.275 40.381 30.204 31.658 32.123 37.727 38.427 37.781 2.6024 0.74358 0.61288
12 124.23 131.96 146.27 3.3817 3.0611 3.3879 1.3262 1.2004 1.3286 36.737 43.109 43.175 31.302 32.691 32.705 37.548 38.413 37.532 2.5943 0.83876 0.64368
13 143.52 149.3 164.52 2.922 2.6763 3.0484 1.1459 1.0495 1.1954 49.116 55.787 53.969 33.824 34.931 34.643 38.817 39.58 38.45 2.3583 0.63626 0.41777
14 156.87 165.76 178.05 3.2507 2.6489 2.7331 1.2748 1.0388 1.0718 48.258 62.577 65.148 33.671 35.928 36.278 37.891 39.669 39.398 2.2933 0.43831 0.99995
15 178.25 184.59 193.3 2.8498 2.474 2.6084 1.1176 0.9702 1.0229 62.548 74.612 74.106 35.924 37.456 37.397 39.035 40.263 39.803 2.1997 0.32357 0.8789
16 193.81 196.97 203.42 2.2181 2.1638 2.6139 0.86985 0.84853 1.0251 87.375 91.029 77.82 38.828 39.184 37.822 41.211 41.427 39.785 1.8003 0.8909 0.42809
⋮
Display a graph of the mean signal and the signal to noise ratio (SNR) of the three color channels over the 20 gray patch ROIs.
figure subplot(1,2,1) plot(noiseTable.ROI,noiseTable.MeanIntensity_R,"r-o", ... noiseTable.ROI,noiseTable.MeanIntensity_G,"g-o", ... noiseTable.ROI,noiseTable.MeanIntensity_B,"b-o") title("Signal") ylabel("Intensity") xlabel("Gray ROI Number") grid on subplot(1,2,2) plot(noiseTable.ROI,noiseTable.SNR_R,"r-^", ... noiseTable.ROI,noiseTable.SNR_G,"g-^", ... noiseTable.ROI,noiseTable.SNR_B,"b-^") title("SNR") ylabel("dB") xlabel("Gray ROI Number") grid on
Measure Noise of Custom Test Chart
Read and display an image of a custom test chart.
I = imread("RGBColorPatches.jpg");
imshow(I)
Draw ROIs for the red, green, blue, and gray patches.
numROIs = 4; roiPos = zeros(numROIs,4); for cnt = 1:numROIs hrect = drawrectangle; roiPos(cnt,:) = hrect.Position; end
Calculate the noise of the ROIs.
noiseValues = measureNoise(I,roiPos)
noiseValues=4×23 table
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 ROIPosition
___ _______________ _______________ _______________ __________ __________ __________ ______________ ______________ ______________ ____________________ ____________________ ____________________ ______ ______ ______ ______ ______ ______ __________ ___________ ___________ ________________________
1 153.13 51.698 75.863 3.6607 3.2828 3.6057 1.4356 1.2874 1.414 41.832 15.748 21.04 32.43 23.945 26.461 36.86 37.806 36.991 2.529 1.0612 1.6642 34 131 59 62
2 78.51 135.38 72.137 4.0934 3.2363 3.9369 1.6053 1.2692 1.5439 19.179 41.83 18.323 25.657 32.43 25.26 35.889 37.93 36.228 2.8095 1.3295 1.4213 41 38 60 63
3 54.715 79.381 185.87 3.025 2.7912 3.5732 1.1863 1.0946 1.4012 18.088 28.44 52.019 25.148 29.078 34.323 38.516 39.215 37.07 2.3571 1.2146 0.7323 136 35 63 66
4 194.31 197.07 203.8 2.184 2.0924 2.5672 0.85645 0.82055 1.0068 88.971 94.184 79.384 38.985 39.48 37.995 41.346 41.718 39.941 1.6667 1.0141 0.51731 161 152 55 60
Input Arguments
chart
— eSFR chart
esfrChart
object
eSFR chart, specified as an esfrChart
object.
im
— Test chart image
RGB image | grayscale image
Since R2024a
Test chart image, specified as an RGB image or a grayscale image.
roiPositions
— ROI positions
n-by-4 numeric array
Since R2024a
ROI positions, specified as an n-by-4 numeric array,
where n is the number of ROIs. Each ROI has the form
[X Y Width Height]
, where X
and
Y
are the coordinates of the top-left corner of the
ROI. Width
and Height
are the width
and height of the ROI, in pixels.
Output Arguments
noiseValues
— Noise values
table
Noise values of ROIs, returned as a table. The table has one row for each measured ROI. The table always has this variable (column):
Variable | Description |
---|---|
ROI | Index of the sampled ROI. |
When the image is an esfrChart
object or an RGB test
chart image, the table has these additional variables:
Variable | Description |
---|---|
MeanIntensity_R | Mean value of red channel pixels in the ROI. |
MeanIntensity_G | Mean value of green channel pixels in the ROI. |
MeanIntensity_B | Mean value of blue channel pixels in the ROI. |
RMSNoise_R | Root mean square (RMS) noise of red channel pixels in the ROI. |
RMSNoise_G | RMS noise of green channel pixels in the ROI. |
RMSNoise_B | RMS noise of blue channel pixels in the ROI. |
PercentNoise_R | RMS noise of red pixels, expressed as a percentage of the maximum of the original chart image data type. |
PercentNoise_G | RMS noise of green pixels, expressed as a percentage of the maximum of the original chart image data type. |
PercentNoise_B | RMS noise of blue pixels, expressed as a percentage of the maximum of the original chart image data type. |
SignalToNoiseRatio_R | Ratio of signal (MeanIntensity_R )
to noise (RMSNoise_R ) in the red
channel. |
SignalToNoiseRatio_G | Ratio of signal (MeanIntensity_G )
to noise (RMSNoise_G ) in the green
channel. |
SignalToNoiseRatio_B | Ratio of signal (MeanIntensity_B )
to noise (RMSNoise_B ) in the blue
channel. |
SNR_R | Signal-to-noise ratio (SNR) of the red channel, in dB.
|
SNR_G | SNR of the green channel, in dB.
|
SNR_B | SNR of the blue channel, in dB.
|
PSNR_R | Peak SNR (pSNR) of the red channel, in dB. |
PSNR_G | pSNR of the green channel, in dB. |
PSNR_B | pSNR of the blue channel, in dB. |
RMSNoise_Y | RMS noise of luminance (Y) channel pixels in the ROI. |
RMSNoise_Cb | RMS noise of chrominance (Cb) channel pixels in the ROI. |
RMSNoise_Cr | RMS noise of chrominance (Cr) channel pixels in the ROI. |
When the image is a grayscale test chart image, im
,
the table has these additional variables:
Variable | Description |
---|---|
MeanIntensity_I | Mean value of pixels in the ROI. |
RMSNoise_I | Root mean square (RMS) noise of pixels in the ROI. |
PercentNoise_I | RMS noise of pixels, expressed as a percentage of the maximum of the original chart image data type. |
SignalToNoiseRatio_I | Ratio of signal (MeanIntensity_I )
to noise (RMSNoise_I ). |
SNR_I | Signal-to-noise ratio (SNR), in dB.
|
PSNR_I | Peak SNR, in dB. |
When you specify a test chart image im
, the table has
this additional column:
Variable | Description |
---|---|
ROIPositions | Position of the ROI, returned as a 4-element vector
of the form [X Y Width Height] .
X and Y are
the coordinates of the top-left corner of the ROI.
Width and
Height are the width and height
of the ROI, in pixels. |
For more information on accessing the measurements within the table, see Access Noise Measurements.
More About
Access Noise Measurements
The order of the variables in the noise table depends on whether you input a test
chart image, im
, or a chart object, chart
.
If you need to access variables of the noise table, refer to variable names and not
numeric indices.
For example, to access the MeanIntensity_R
variable of the
noise table, use code such as this.
mean_R = noiseValues.MeanIntensity_R;
For another example, to access the peak SNR values of the ROI with index 3, use
code such as this. The first command returns the PSNR_R
,
PSNR_G
, and PSNR_B
variables in a table
for the ROI with index 3. The second command converts the table into a numeric row
vector.
psnr_RGB_3 = noiseValues(noiseValues.ROI==3,["PSNR_R" "PSNR_G" "PSNR_B"]); psnr_RGB_3 = psnr_RGB_3{1,:};
Note that you can perform these two operations in a single command:
psnr_RGB_3 = noiseValues{noiseValues.ROI==3,["PSNR_R" "PSNR_G" "PSNR_B"]}
For more information, see Access Data in Tables and Access Data in Cell Arrays.
Tips
To linearize data for noise measurements, first undo the gamma correction of an sRGB test chart image by using the
rgb2lin
function.
References
[1] Imatest. "Esfr". https://www.imatest.com/mathworks/esfr/.
Version History
Introduced in R2017bR2024a: Support for additional test charts
You can now measure the noise of ROIs for additional types of test charts:
Grayscale images of test charts.
Test charts other than the Imatest Enhanced or Extended eSFR test chart.
To measure the noise for additional types of test charts, specify the test chart
image, im
, and the position of the ROIs,
roiPositions
.
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