hx_fill_interlace — 2D halcon_ext op

• Data kinds: image → image

• Call: fullseye.apply(img, "hx_fill_interlace", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: fill_interlace (the HALCON reference is a useful guide to its meaning and parameters)

hx_fill_interlace: input → output

*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*

*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ hx_fill_interlace: other inputs (docs site)

*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*

Usage

Interpolate two video half-frames (replace the odd rows by the mean of the adjacent even rows = de-interlacing).

Treats 1 image as 2 fields of odd and even rows, and replaces the odd rows (1::2) with the mean of the adjacent rows above and below 0.5*(v[i-1] + v[i+1]). Even rows are left as-is. The output is a float image of the same shape as the input.

• a, b are unused.

• The rows above and below are taken with np.roll, so when the height is even, "below" the last row (an odd row) is the first row (only the 1 edge row wraps around).

The simplest linear interpolation for removing the comb-like misalignment of interlaced video; the information of the odd field is discarded (vertical resolution drops to half). You cannot choose which field to keep (the even rows always survive). As preprocessing when row-direction stripes are suspected, place it before derivative-type ops such as hx_nonmax_dir.

Border handling: wrap around to the opposite side (periodic) (measured; tools/impl2/border_probe.py).

Detailed usage guide

• gallery2d_halcon_ext 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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

hx_fill_interlace 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (halcon_ext)

hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_gabor · hx_fit_surface1 · hx_fit_surface2


*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.