I’m really not able to follow the code here, but it looks like the same sort of idea. I’m assuming that’s a 16x16 tf?
The output seems to be more strongly dominated by primaries and secondaries than I’d expect, so I’m not sure if there’s a difference in our approaches. Then again, it’s hard to tell when things are random…
I hate to ask, but for sake of making sure we’re on the same page regarding the 2D interpolator, could you do me a favor and if possible, run a test pair with a fixed tf for normal and hard variants of your setup? I’m really lost in g’mic.
% 4x4x3 tf. i assume you'd need to convert to int
tf_r=[0.46793 5.1692e-06 0.87901 0.61863 0.40424;0.26789 0.19705 0.13195 0.83972 0.35911;0.07158 0.14952 0.64716 0.76896 0.21964;0.94989 0.76023 1 0.22937 0.98994;0.8272 0.13955 0.13179 0.08721 0.35122]
tf_g=[0.79758 0.38628 0.080147 0.87035 0.053319;0.74359 0.22975 0.026048 0.56244 0.79968;1 0.57999 0.82849 0.031294 0.44134;0.49606 0.82131 0.35239 0.0477 0.65466;0.46792 0 0.4475 0.87378 0.52436]
tf_b=[0.48131 0.1731 0 0.47259 0.53728;0.54483 0.44578 0.95829 0.80938 0.16761;1 0.23373 0.96989 0.78254 0.70184;0.47504 0.2867 0.85657 0.36321 0.0074168;0.27969 0.76006 0.20659 0.019315 0.60487]
tf=cat(3,tf_r,tf_g,tf_b);
% normal and hard modes
ashes1=imblend(fg,bg,1,'mesh',tf);
ashes2=imblend(fg,bg,1,'hardmesh',tf);
…and of course, a lot of fun with horribly-compressed JIFFs.
Exploiting processing error sources to produce remotely-referential derived images? Now we’re talking!