Add Gaussian multilooking option for phase linking - #734
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- Add ShpMethod.GAUSSIAN enum value - Create _gaussian.py module that generates Gaussian weights using JAX - Update shp/__init__.py dispatcher to handle GAUSSIAN method - Modify covariance.coh_mat_single to support both boolean masks (GLRT/KS) and float weights (Gaussian) by converting to unified float handling - Add tests for Gaussian weight generation and comparison with RECT The Gaussian multilooking option provides a simpler alternative to GLRT that applies a 2D Gaussian window for weighting neighbors during coherence estimation. Unlike adaptive methods (GLRT/KS), it uses a fixed weight pattern for all pixels. https://claude.ai/code/session_01NtLGb8epFAKDEVgqY8HxdU
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Summary
Adds a
GAUSSIANSHP method: a fixed 2D Gaussian window for weighting neighborsduring coherence estimation, as a simpler alternative to the adaptive GLRT/KS
tests. Unlike the adaptive methods, it applies the same weight pattern to every
pixel.
Changes
ShpMethod.GAUSSIANenum value.shp/_gaussian.pygenerating Gaussian weights (JAX).shp/__init__.pydispatcher handles theGAUSSIANmethod.covariance.coh_mat_singleaccepts both boolean masks (GLRT/KS) and floatweights (Gaussian) via unified float handling.
shp_countsnow reports the effective number of looks (ENL) for float-weightmethods via Kish's formula
ENL = (sum w)^2 / sum(w^2), instead of a rawneighbor count (which is only meaningful for boolean SHP).
Tests
New tests in
test_shp.py,test_phase_link_covariance.py,test_phase_link_core.pycovering Gaussian weight generation and comparisonwith RECT/boolean methods. All pass.
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