Seiza / Observing report

Project analysis

Frame measurements & integration diagnostics

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Self-contained · offline ready

Compare frames within one pointing and filter.
Processing outcomes describe participation, not image quality.

Integration depth

Measured noise against an independent-frame comparison

Measured split noiseIdeal 1/√N comparison

Frame health

Inspect variation; use combined metrics to assess quality

Measured framePartial measurementGroup median

Frame measurements

Open a filename for its path, registration details and advisories.

Frame / detailsMeasurementDepthExposure sStarsHFR pxFWHM pxEccentricityPeak SNRNoise

Processing time

What the timings include

Wall-clock seconds, including failed attempts. Measurement includes conversion, quality detection, PSF fits and native noise/background. Registration includes its own star detection. Sampling includes normalization and temporary writes. Total includes overhead, but excludes report rendering and writing. Stage times do not overlap.

Method & interpretation

Advisories never automatically exclude a frame. A high SNR or star count alone is not a quality verdict.

    Assumptions & limitations

      Full-depth analysis uses non-overlapping 16×16 patches at two-component-sample pitch in the central 80%. Only patches valid in every depth-included frame contribute. Noise is median patch MAD × 1.4826 of (odd sum − even sum)/N; at least 32 common patches are required. Odd depths have no split measurement. Shared systematic errors cancel; robust noise describes the distribution core, not total outlier energy.

      The ideal 1/√N comparison assumes independent, equal-quality frames and is anchored at two frames. Trend fits use geometric even-depth checkpoints over the last fourfold window. Cumulative observations are correlated: R² is descriptive, not a confidence interval. Any conditional estimate assumes the fitted trend persists.