Sequential Constraint Reduction Under Persistent Uncertainty: A Governed Method for Ambiguous Image-Based Investigation

Ambiguous image investigations can produce reproducible measurements without sufficient authority for interpretation. Sequential constraint reduction separates observation, constraint, measurement, comparison, contradiction and negative space, next-question selection, bounded interpretation, truth-state update, and stop or transfer. A retrospective satellite-imagery case near Nikumaroro preserves historical exploration beside a corrective branch governed by source identity, strict ROI validity, balanced coverage and claim reconciliation. Six frozen local image layers designated Band07 and fixed 128 × 64 windows yield a lower candidate mean normalized Sobel-gradient score than the four-control median in 6/6 baseline observations, every year-omission subset and 24/24 control omissions. Of 54 planned year-by-placement cases, 51 are evaluable: six baseline placements and 45 nonbaseline shared shifts. All 51 preserve the median-relative direction; strict below-all-controls separation passes 6/6 at baseline and 46/51 placements, with five strict exceptions and three unevaluable cases. The same images and overlapping windows are reused. Final envelopes in some retained runners were serialized after computation, so complete prospective enforcement is not demonstrated. Spectral identity and extraction lineage remain unresolved. The analysis establishes no physical identity, historical association, uniqueness, causality, significance or lock status. The integrated contribution is a corrective workflow linking preserved exploratory history to bounded claim authority and machine-readable stopping, demonstrated in one case whose broader performance remains unvalidated.