Cartoonization_Mathematica_code.txt

img = Import["frame.jpg"];
{ltemp, atemp, btemp} = ColorSeparate[img, "LAB"];
bImg = BilateralFilter[img, 2, 1];
{l, a, b} = ColorSeparate[bImg, "LAB"];
ldata = ImageData[l];
q = 6;
qnearest = {0, 0.2, 0.4, 0.6, 0.8, 1};
expr = Nearest[qnearest, ldata[[600, 600]]];
qnearestdata = ldata;
{w, h} = ImageDimensions[l]
For[i = 1, i <= h, i++,
  For[j = 1, j <= w, j++,
   qnearestdata[[i, j]] = Nearest[qnearest, ldata[[i, j]]][[1]]]];
lgrad = GradientFilter[ltemp, 1];
gradRange1 = 0;
gradRange2 = 2;
sharpRange1 = 0.3;
sharpRange2 = 1.4;
lumGradFunc =
  ImageData[
   lgrad *((sharpRange2 - sharpRange1)/(gradRange2 - gradRange1)) +
    sharpRange1];
quantizedImage =  
  0.1* Tanh[lumGradFunc (ldata - qnearestdata)] + qnearestdata;
qImg = Image[quantizedImage, ImageSize -> 300]
res = ColorCombine[{qImg, a, b}, "LAB"]
finalq = ColorConvert[res, "RGB"]
imgE = ColorConvert[img, "Grayscale"];
grayDat = ImageData[imgE];
grad = GradientFilter[img, 2]
tau = 0.998;
k = 2;
ap = 0.45;
bp = 0.1;
gradDat = ImageData[ImageAdjust[grad]];
DOG = gradDat;
For[i = 1, i <= h, i++,
  For[j = 1, j <= w, j++, delta = Log[ap, gradDat[[i, j]]] + bp;
   If[delta == Infinity, DOG[[i, j]] = 0,
    DOG[[i, j]] = (1/Sqrt[2*Pi])*Abs[1 - (tau/k)]*(1/delta)]]];
edgeDetected = ImageAdjust[Image[DOG, ImageSize -> 500]];
cartoonizedImage = finalq - edgeDetected;