vx_sobel3x3 — VX `gradient` op

• Data kinds: image2d → table

• Call: import fullseye as fs; fs.ledger.vx_sobel3x3(image, *, border, constant_value=0) (to call the implementation directly, import vxcore; vxcore.vx_sobel3x3(image, *, border, constant_value=0); from the registry, opsvx.get("vx_sobel3x3"))

Usage

Sobel 3×3 (Section 3.46): applies G_x = [[−1,0,1],[−2,0,2],[−1,0,1]], G_y = [[−1,−2,−1],[0,0,0],[1,2,1]] (REQ-0415) as a correlation.

*image*: U8. *border* (required): "replicate" / "constant" (filled with *constant_value*) / "undefined" (the outermost 1 pixel is undefined by the specification -- 0 is put there and it is returned as outside valid).

Return value {"gx": S16, "gy": S16, "valid": (y0, y1, x0, x1)} (the U8 3×3 Sobel has |value| ≤ 1020, so S16 does not saturate).

Raises ValueError: not a 2-D U8 / border not in the list / constant_value outside 0 to 255.

Detailed usage guide

• openvx_ports family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept `table` as input)

—

Same category (`gradient`)

vx_magnitude · vx_phase

*Provenance: vxcore.py — VX operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

vx_sobel3x3 — VX gradient op