On Monday 12 December 2005 20:54, Gary Laevsky wrote:
> Our homemade system has some inherent noise in the PMT, to the tune
> of about 1000 pixels out of 30,000 or so. I'd like to "delete" the
> 255s. In many cases, the next pixel value is about 150, so I'm also
> having some "stretch" issues. If I could just delete the 255s....
Not sure if these 3 options would to what you want, but be aware that these
methods "invent" values for the noisy pixels...
A) simplest:
* duplicate original and call it image1
* threshold the image1 at 255,255
* subtract original-image1 (pixels at 255 will now be 0).
B) 8 bit & 24 bit image denoising
////////////////////////////////////////////////////////////////////////////
// SaturatedSinglePixelDenoising.txt
// G. Landini 16/July/2005
// This macro detects saturated *single* pixels (8 connected) in the
// image (grey=255) and replaces them with the pixel value of
// either the mean or the median of the neighbours (choose which
// method one by un-commenting the lines indicated below.
// Works with 8bit and 24 bit images only.
// Needs the Particles8 plugin available at:
// http://www.dentistry.bham.ac.uk/landinig/software/software.html
run("Duplicate...", "title=Denoised");
setBatchMode(true);
run("Duplicate...", "title=pixels");
if (bitDepth==24) run("8-bit");
setThreshold(255, 255);
run("Threshold", "thresholded remaining");
//---
// if you want to denoise small clusters of pixels, rather than single pixels,
// then comment the following 5 lines, but be aware that the average
// or median will not be correct as other pixels in the cluster may
// contribute to the corrected value:
run("Duplicate...", "title=non-single");
run("Particles8 ", "white show=Particles filter minimum=2 maximum=999999
overwrite");
imageCalculator("Subtract", "pixels","non-single");
selectWindow("non-single");
close();
//---
selectWindow("Denoised");
run("Duplicate...", "title=median");
// use average of the 8 neighbours
run("Convolve...", "text1=[1 1 1 1 0 1 1 1 1] normalize");
// use median of the 3x3 neighbourhood
//run("Median...", "radius=1");
if (bitDepth==24){
selectWindow("pixels");
run("RGB Color");
}
imageCalculator("AND create", "pixels","median");
imageCalculator("Subtract", "Denoised","pixels");
imageCalculator("Add", "Denoised","Result of pixels");
selectWindow("median");
close();
selectWindow("Result of pixels");
close();
selectWindow("pixels");
close();
setBatchMode(false);
////////////////////////////////////////////////////////////////////////////
C) 8 bit images only denoising
////////////////////////////////////////////////////////////////////////////
// SaturatedPixelsDenoising.txt
// G. Landini 16/July/2005
// This macro detects saturated pixels (8 connected) in the
// image (grey=255) and replaces them with the pixel value of
// the mean of the neighbours which are not saturated..
// Works with 8bit images only.
// Needs the BinaryConnectivity plugin available at:
// http://www.dentistry.bham.ac.uk/landinig/software/software.html
t=getTitle();
if (bitDepth()==24){
run("RGB Stack");
setSlice(1);
denoiser();
selectWindow("Denoised");
rename("red");
selectWindow(t);
setSlice(2);
denoiser();
selectWindow("Denoised");
rename("green");
selectWindow(t);
setSlice(3);
denoiser();
selectWindow("Denoised");
rename("blue");
run("RGB Merge...", "red=red green=green blue=blue");
rename("Denoised");
selectWindow(t);
run("RGB Color");
}
else {
if (bitDepth()==8) denoiser();
}
function denoiser () {
run("Duplicate...", "title=Denoised");
setBatchMode(true);
xe=getWidth();
ye=getHeight();
cycle=true;
while (cycle){
selectWindow("Denoised");
run("Duplicate...", "title=pixels");
setThreshold(255, 255);
run("Threshold", "thresholded remaining");
selectWindow("Denoised");
run("Duplicate...", "title=median");
// use average of the 8 neighbours
run("Convolve...", "text1=[1 1 1 1 0 1 1 1 1] normalize");
imageCalculator("AND create", "pixels","median");
imageCalculator("Subtract", "Denoised","pixels");
imageCalculator("Add", "Denoised","Result of pixels");
selectWindow("median");
close();
selectWindow("Result of pixels");
close();
selectWindow("pixels");
run("BinaryConnectivity ", "white");
cycle=false;
for (x=0;x<xe;x++){
for (y=0;y<ye;y++){
n=getPixel(x,y);
if (n>1){
if(n<9){
selectWindow("Denoised");
putPixel(x,y,(getPixel(x,y)*8 - ((n-1)*255))/(9-n));
updateDisplay();
selectWindow("pixels");
}
else cycle=true;
}
}
}
selectWindow("pixels");
close();
}
setBatchMode(false);
updateDisplay();
}
////////////////////////////////////////////////////////////////////////////
Cheers,
Gabriel
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