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Alpha by colour projection gives backdrop noise a few per cent, and a blur spreads it: zero it within the noise

Rule

If a cut-out has a faint fuzz a few pixels wide on the opposite ground, backdrop noise got alpha: zero it within B's noise, smooth only inwards, clamp the edge colour both ways.

Snippet
# before: the projection everywhere in the band, then a 3x3 Gaussian
a = np.clip(((f - B) * fb).sum(-1) / np.maximum(denom, 1e-3), 0, 1)
alpha = cv2.GaussianBlur(alpha, (3, 3), 0)
# after: backdrop within its noise is backdrop; the outline loses its steps without growing a fringe
a = np.where(np.sqrt(((f - B) ** 2).sum(-1)) < 7.0, 0.0, a)
alpha = np.minimum(alpha, cv2.GaussianBlur(alpha, (0, 0), 0.55))
C = np.clip(C, F - rim_allow, F + rim_allow)  # brighter is a halo at night, darker a line by day
Check

Read a column of alpha values across the edge, over pixels that are plainly backdrop: they are 0.

Applies to

other: per-pixel alpha estimation by colour projection (NumPy and OpenCV)

I assumed

pixels that are the backdrop project to alpha 0 anyway, so a light blur only smooths the outline.

What happened

on the dark wall a yellow puffer's collar had a dark fuzz three pixels wide. The pixels there were the backdrop exactly (L* 70 to 73 against 70), but the projection gave each 1 to 10%, and the blur spread them by another pixel.

The fix

a pixel within 7 RGB levels of the backdrop is backdrop, whatever the projection says. The outline is smoothed only inwards, min(alpha, blur(alpha)), and the edge colour is clamped both ways against the material inside: brighter would be a halo on the night wall, darker a line on the day wall.

Evidence

commit a8babd6; the column through the collar went from alpha 3, 14, 25, 82 (in %) over backdrop pixels to 0.

Learned in the articleCutting AI garment pictures so they hang true: a signed key, hook points and shadows for a CSS rail

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