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New xrspatial.glcm module with glcm_texture() for computing Haralick texture features (contrast, dissimilarity, homogeneity, energy, correlation, entropy) over a sliding window. Supports numpy, dask+numpy, cupy, and dask+cupy backends. Dask path pre-quantizes globally for consistent gray-level mapping across chunks.
29 tests covering validation, quantization, known-value checks, NaN handling, edge cases, all six metrics, angle averaging, and cross-backend consistency (numpy vs dask, cupy, dask+cupy).
Add glcm_texture to the focal reference docs and to the README feature matrix. CuPy/Dask+CuPy marked as CPU-fallback.
Demonstrates single/multi metric usage, angle effects, Dask support, and parameter reference on a synthetic four-texture raster.
brendancol
added
enhancement
Standalone script with a six-zone synthetic raster. Keyboard controls cycle through metrics, window sizes, gray levels, and angles. Clicking a pixel shows its local GLCM matrix and a bar chart of all six Haralick feature values.
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Summary
New
glcm_texture()function inxrspatial/glcm.py, per #963.Computes six Haralick GLCM metrics (contrast, dissimilarity, homogeneity, energy, correlation, entropy) over a sliding window. Pass a single metric name for a 2-D result, or a list for a 3-D result with a leading
metricdimension.Backends:
map_overlapcupy.asnumpyParameters:
window_size(odd, >= 3),levels(2-256),distance(pixel pair spacing),angle(0/45/90/135 or None to average all four).Other changes:
docs/source/reference/focal.rstexamples/user_guide/22_GLCM_Texture.ipynb)__init__.pyand.xrsaccessorCloses #963
Test plan
pytest xrspatial/tests/test_glcm.py-- 29 tests pass