I have a grey scale image (1600*480 pixels, 8 bit): https://i.imgur.com/BqgJRv7.png (update)

I want to determine the number of overexposed pixels in each column. Then I want to plot the a combined plot which is containing the image and the plot showing the number of overexposed pixels together with a smoothed curve.

Is this the right way how I did it? Can something be improved/corrected?

dim = ImageDimensions[image];

xaxis = Range[dim[[1]]];

overexposedPixelsPerColumn = 
        ImageTake[image, {1, dim[[2]]}, {#, #}], "IntensityData"]], 
     brightness_ /; brightness == 1.] & /@ Range[dim[[1]]];

totalOverexposedPixels = Total@overexposedPixelsPerColumn;

maxOverexposedPixelsPerColumn = Max@overexposedPixelsPerColumn;

nPoints = 50;

smoothedOverexposedPixelsPerColumn = 
  MovingAverage[overexposedPixelsPerColumn, nPoints];

  ListLinePlot[Transpose[{xaxis, overexposedPixelsPerColumn}], 
   InterpolationOrder -> 1, PlotStyle -> {LightGray}, 
   Epilog -> {{PointSize[Large], 
      Point[Transpose[{xaxis, overexposedPixelsPerColumn}]]}, 
     Inset[image, Scaled[{.5, 1}], Automatic, Scaled[1]]}, 
   Frame -> True, 
   FrameLabel -> {{"# of overexposed pixels per column", 
      ""}, {"column", 
      StringJoin["red curve: moving average over ", ToString[nPoints],
        " pixels", "; total # of overexposed pixels=", 
   PlotRange -> {All, 
     MinMax@(overexposedPixelsPerColumn) + {0, 
   BaseStyle -> {FontWeight -> "Bold", FontSize -> 35, 
     FontFamily -> "Calibri"}, ImageSize -> 2000, 
   ImagePadding -> {{All, All}, {All, 50}}, 
   PlotStyle -> {Blue, Thick}, AxesStyle -> Thick, 
   FrameStyle -> Thick],
   Transpose[{xaxis[[nPoints/2 ;; Length@xaxis - nPoints/2]], 
   PlotStyle -> {Red, AbsoluteThickness[3]}]

enter image description here


It is hard to assess "IntensityData" from ComponentsMeasurements because I failed to find anything but a small entry in details section about it.

My comment was only slightly off, since Binarize treats the second parameter inclusively, that is 1. means anything <=1. will be 0 then the result is a black image. To exclude 1. we can flip it with ColorNegate:

img = Import @ "https://i.imgur.com/lPdFDcm.png";

data = Total /@ 
    Transpose @ ImageData@ColorNegate@Binarize[ColorNegate@img, 0.] // N;
data // Total

 data, AspectRatio -> 1/3, ImageSize -> 600

enter image description here

Let me know if I made a mistake and I will delete the answer. If you find it more trustworthy I will try to update it later.

  • $\begingroup$ What confuses me Dimensions[data] is 1413 instead of 1600. Ah, I see I uploaded the png file directly from the notebook with wrong size. I have now uploaded the one with 1600*480 pixels, see the link https://i.imgur.com/BqgJRv7.png. Sorry for the mistake. If I now use your code with this image it produces exactly what I got, when I use ListPlot[data, AspectRatio -> 1/3, ImageSize -> 600, PlotRange -> All]. Thank you for the solution. May be you can update your solution with the new file ... $\endgroup$ – mrz Nov 6 '18 at 14:24

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.