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macro:autofocus_hyperstack
// Autofocus hyperstack macro
// Select the in focus frame from each slice of a hyperstack and create a new stack
// of just the in focus frames

// Based on algorithm F-11 "Normalized Variance"
// In: Sun et al., 2004. MICROSCOPY RESEARCH AND TECHNIQUE 65, 139–149.
// And the original macro by Andy Weller http://imagejdocu.tudor.lu/doku.php?id=macro:normalized_variance

setBatchMode(true);

//Get image type
type = bitDepth();
if (type==8) {type="8-bit";} else {if(type==16) {type="16-bit";} else{if(type==32) {type="32-bit";} else {if(type==24) {type="RGB";}}}}

StackID=getTitle();
Stack.getDimensions(width, height, channels, slices, frames);

if (channels>1) {exit("The hyperstack has 2-channels please reduce dimensionality")} else{}

for (k=1; k<=frames; k++) { Stack.setFrame(k);
m=0;
normVar = 0; // Set to 0 which is out of focus
for (l=1; l<=slices; l++){
selectWindow(StackID);
Stack.setSlice(l);

getRawStatistics(nPixels, mean);
W = getWidth();
H = getHeight();
b = 0;

for (j=0; j<H; j++) {
for (i=0; i<W; i++) {
p = getPixel(i,j);
t = (p-mean)*(p-mean);
b += t;
}
}

if ((b/(H*W*mean))>normVar) {normVar = (b/(H*W*mean)); m++;} else {normVar=normVar;}

}

Stack.setSlice(m);
run("Select All");
run("Copy");
if (isOpen("Output")){
selectWindow("Output");
}
else{
newImage("Output", type, width, height, 1);
}
run("Paste");
selectWindow(StackID);
Stack.setSlice(l);

}
setBatchMode("exit and display");
//Richard Mort 27/09/2018