Top hat filter

The top_hat filter can be used to detect the relatively small edges/peaks superimposed on large background signals. The concept came from the EELS workshop during IMC19. Thanks to Prof. Nestor J. Zaluzec.

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// Using Top_hat digital filter to detect the  relatively small edges 
//    superimposed on large background signals.
//
// ref: Ultramicroscopy 18 (1985) 185-190 
//      Digital Filters  for Application to Data Analysis in EELS
//      by Nestor J. ZALUZEC

// Parameters:
// win_s: signal window (default:3)
// win_b: background window (default:3)
//  a_s : amplitude of signal (fixed value)
//  a_b : amplitude of background  (fixed value)

// Renfong 2018/10/11

// Main function
image Top_Hat_Filter(image img, number win_s, number win_b)
{
// read image
string fname=img.GetName()
number sx,sy
img.getsize(sx,sy)

// filter
image img2 := imageclone(img)*0

//the area between signal and background must be equal
number a_s=1
number a_b=a_s/(2*win_b/win_s)

number i
for(i=-1*(win_s-1)/2;i<=(win_s-1)/2;i++)
{
img2=img2+a_s*img.offset(i,0)
}

for(i=0;i {
img2=img2-a_b*img.offset(-1*(win_s+1)/2-i,0)
img2=img2-a_b*img.offset(1*(win_s+1)/2+i,0)
}

img2=tert(icol<(win_s-1)/2+win_b,0,img2)

img2=tert(icol>=(sx-(win_s-1)/2-win_b),0,img2)
img2.setname("TH-Filter of " + fname)
img2.showimage()
img2.ImageCopyCalibrationFrom(img)
img2.ImageSetIntensityUnitString( "a.u." )
return img2
}

// Main script
image img := GetFrontImage()
number win_s = 3
number win_b = 3

Top_Hat_Filter(img,win_s,win_b)

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Test results