denoise_gaussian_2d¶

Separable isotropic Gaussian smoothing of ctx.image.

scipy.ndimage.gaussian_filter(sigma), default mode 'reflect'. Isotropic — the same σ is applied to rows and columns. For anisotropic smoothing, pass a tuple via the underlying scipy API directly.

Parameters¶

Use it¶

from spectro_kernel import run_algorithm

output = run_algorithm("denoise_gaussian_2d", ctx, {
    "sigma": 0.0
})

{
  "tool": "denoise_gaussian_2d",
  "arguments": {
    "session_id": "<session_id>",
    "params": {
      "sigma": 0.0
    }
  }
}

References¶

• Lindeberg 1994, Scale-Space Theory in Computer Vision (Kluwer).
• scipy.ndimage.gaussian_filter — separable Gaussian implementation.

Related algorithms¶

• correct_slant_affine - Make monochromatic lines parallel to the rows by a horizontal shear.
• correct_smile_polynomial - Undo smile curvature via the Schroeder even-order expansion.
• correct_tilt_affine - Re-align the slit with the detector columns by a vertical shear.
• dark_subtract - Subtract a master dark from ctx.image.
• denoise_median_2d - Square median filter over ctx.image, optionally banded by rows.
• flat_normalize - Divide ctx.image by a master flat normalised to unity.
• flat_normalize_easyspec - Flat-field correct a science frame via cleaning.flatten.
• outlier_rejection_mad_adaptive - Replace pixels whose deviation from a local median exceeds threshold·MAD.
• subtract_bias_easyspec - Subtract a master bias from a single science frame via cleaning.debias.
• subtract_dark_easyspec - Subtract a master dark from a science frame via cleaning.sub_dark.
• subtract_sky_2d - Subtract a per-column sky model fitted from off-trace rows of ctx.image.