Median filter? Use it to «thin out» bad pixels that appear locally sparse (for some definition of «local»). Then count the remaining bad pixels.

Median filter? Use it to «thin out» bad pixels that appear locally sparse (for some definition of «local»). Then count the remaining bad pixels.

Or convolve with a large-ish 2d kernel (eg flat rectangular window) and decimate to get a number for «how many bad pixels are there inside each eg 16x16 window». Then accumulate the score for each block in a nonlinear fashion (so as to punish really dense blocks).

Im = randi([0 1], 640, 480);

Im_lp = conv2(ones(16), Im);

Im_lp_dec = Im_lp(8:16:end, 8:16:end);

score = sum(Im_lp_dec(:).^2);