stopping op• Data kinds: image2d → table
• Call: import fullseye as fs; fs.ledger.iv_richardson_lucy_until(image=None, psf_sigma=1.5, psf=None, noise='poisson', sigma=None, gain=1.0, tau=1.0, max_iter=2000, plateau_window=25, plateau_rtol=0.0001, keep_history=True, callback=None) -> 'dict' (to call the implementation directly, import deconvstop; deconvstop.iv_richardson_lucy_until(image=None, psf_sigma=1.5, psf=None, noise='poisson', sigma=None, gain=1.0, tau=1.0, max_iter=2000, plateau_window=25, plateau_rtol=0.0001, keep_history=True, callback=None) -> 'dict'; from the registry, opsconverge.get("iv_richardson_lucy_until"))
Richardson-Lucy deconvolution stopped by the discrepancy principle (Poisson: Bertero 2010, tau = 1; Gaussian: Morozov); refuses data outside the model's range.
image: the blurred, noisy 2-D image. psf: a 2-D PSF (normalised here), or a Gaussian of psf_sigma px. The blur is periodic (FFT), so the RL step x <- x * H^T(y / H x) keeps sum(H x) = sum(y) exactly (Lemma 3.2 of Benvenuto & Piana).
• noise="poisson": image * gain must be photon counts (non-negative integers within 1e-6); stop at the first k with the Poisson discrepancy D_k <= tau (Benvenuto & Piana 2012 eq. (30); tau = 1 as proposed by Bertero et al. 2010).
• noise="gaussian": sigma (the noise standard deviation, in image units) is required; stop at the first k with ||H x_k - y||^2 / (N sigma^2) <= tau (Morozov, eq. (18)). The image must be non-negative (add the known offset first).
The iteration starts from the flat image of the data's mean (k = 0). Returns image (x_k in the input units), stopped, status, k_stop, discrepancy_history (D_0, D_1, ...), mass_rel_error_max (Lemma 3.2), tau and noise.
Not stopped -> image = None and status:
• "outside_model_range" — the discrepancy levelled off above tau (relative decrease below plateau_rtol per iteration over plateau_window iterations): y is not in the range of the model, so the criterion can never be met (Benvenuto & Piana: the rule is a regularisation iff y is in H(C)). Typical causes: the assumed PSF is wider than the real blur, a background is missing, the noise level is wrong.
• "max_iter" — still decreasing when max_iter ran out.
The last iterate is under last_iterate (not an estimate). callback(k, x_k, D_k), if given, is called after every iteration (x_k in the input units) — for plotting the run.
• convergent_computation family guide
• 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.
• converge_tour — py -3.11 examples/converge_tour.py
table as input)—
stopping)—
*Provenance: deconvstop.py — CONVERGE 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.