So I took your image and ~~ruined my MATLAB account~~ used the most normal part of your totally normal cow as a 3D [1] ~~cockvolution~~ convolution kernel. So in some sense, I dragged the red and purple part all across your image and added up the results. Here's the result:

Figure 2024-01-15 14_46_27

Here's the MATLAB code:

normal_image = imread("totally_normal_image.png");

feature=normal_image(272:350,205:269,:);

feature_expansion = padarray(feature,[0,ceil((79-65)/2),0],'replicate');

for m = 1:1:3
new_normal_image(:,:,m) = conv2(normal_image(:,:,m),feature_expansion(:,:,m));

new_normal_image(:,:,m) = new_normal_image(:,:,m)/max(max(new_normal_image(:,:,m))); 
end

imshow(new_normal_image)

[1] The original image was practically grayscale, so only a 2D convolution is required, i.e. over 2 spatial dimensions. Since you added color, it adds a extra dimension, one per color channel. Which makes it more annoying to work with in MATLAB. I mean, I could have just dumped everything into grayscale, but I need practice with processing color images anyways.