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Image Inpainting (masked region recovery) L1-384

Signal ProcessingSpatial hole-filling / occlusion removalδ=3 · standardL_DAG = 2📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

A binary mask M removes pixels from the image x (unknown pixels replaced by a sentinel); the task recovers x in the masked region using surrounding context and a natural-image prior.

L-DAG

D.mask.spatial -> int.spatial
D.mask.spatialint.spatial

Well-posedness W

Existence:
true
Uniqueness:
false
Stability:
conditional
κ:
10000

Strictly underdetermined inside mask; uniqueness is prior-induced (TV, non-local similarity, learned). Stability decreases super-linearly with mask_ratio and hole diameter.

Solvability C

Solver class:
PDE diffusion (Bertalmio), exemplar-based (Criminisi), total-variation (TV), patch-match, learned (DeepFill, partial-conv, LaMa, MAT)
Convergence rate q:
2
Complexity:
PDE O(H*W*iterations); patch-match O(H*W*P); learned single forward O(H*W*C*F)

Specs (0)

No L2 specs registered yet for this principle.