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hyperproc.correct¶
Source-derived reference
Generated from the current hyperproc 0.1.2 checkout.
Implementation: hyperproc/correct/__init__.py. Signatures, defaults, docstrings, and expandable source are extracted statically; the module is not imported or executed. Names beginning with _ are implementation details, not a stable public API.
Use the function signature as the authority for individual parameter defaults and return annotations. Original docstrings sometimes group parameter names or wrap return descriptions across lines; these descriptions are preserved rather than inferred or rewritten.
Exported entry points¶
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Topographic and BRDF correction for the cubes the readers return.
The math lives in small, separately testable modules:
- :mod:
hyperproc.correct.kernels- Ross and Li BRDF kernels. - :mod:
hyperproc.correct.topo- cosine, C, SCS and SCS+C corrections and the illumination-dependence diagnostic that decides whether to apply one. - :mod:
hyperproc.correct.brdf- FlexBRDF: per-NDVI-bin kernel fits pooled across a group of images, applied as a nadir normalisation. - :mod:
hyperproc.correct.mcd43- MODIS MCD43A1 BRDF model parameters, fetched for a scene's footprint and date. - :mod:
hyperproc.correct.cfactor- the c-factor normalisation for satellite scenes, which borrow their BRDF shape from MODIS because one overpass cannot measure it. - :mod:
hyperproc.correct.masks- the pixel masks the fits are drawn from. - :mod:
hyperproc.correct.coefficients- wavelength-keyed coefficient files with fit diagnostics and provenance. - :mod:
hyperproc.correct.pipeline- sample -> fit -> apply -> export on real airborne cubes (NEON, AVIRIS), with the gates that decide whether a correction is warranted. A satellite scene has no angular spread to fit, so it goes through :mod:~hyperproc.correct.cfactorinstead.
Everything here is written from the primary literature and checked against
synthetic data with known answers (tests/test_correct_*.py) and against
an independent implementation on real NEON flightlines.