# This file contains metadata for your plugin
[general]
name=HyperSpectral Processer
qgisMinimumVersion=3.0
qgisMaximumVersion=4.99
description=Local, GPU-accelerated hyperspectral processing in QGIS: spectral indices, PCA, and Spectral Angle Mapper target detection via an external C++/OpenMP/OpenCL engine.
version=1.0.0
author=Aaron R
email=aaronr43210@gmail.com
about=Single-purpose, local-first QGIS plugin from Digital University Kerala for hyperspectral image processing. It drives an external C++/OpenMP/OpenCL engine to process hyperspectral rasters entirely on local hardware, writing results as GeoTIFF or VRT layers and loading them straight into the QGIS canvas. All per-pixel math runs in the native engine to keep large scenes off the Python heap. The plugin ships binary-free: the engine is located at run time from a configured path, the system PATH, or built from the bundled hpc-engine source.
 .
 Three operations are selectable from one uncluttered dialog: (1) Spectral indices - NDVI, NDWI, NDBI, SAVI, EVI, NDMI and MSAVI; (2) PCA - principal-component dimensionality reduction producing false-colour PC composites (covariance or correlation matrix); (3) SAM - Spectral Angle Mapper reflectance-based target detection from a reference pixel picked on the map, with an optional detection mask and similarity band. Compute runs on the GPU through OpenCL where available, with automatic multi-core CPU fallback that produces identical results.
category=Raster
experimental=True
tracker=https://github.com/aaron43210/HYPERSPECTRAL_DATA_DISTRIBUTED_SYSTEM/issues
repository=https://github.com/aaron43210/HYPERSPECTRAL_DATA_DISTRIBUTED_SYSTEM
homepage=https://github.com/aaron43210/HYPERSPECTRAL_DATA_DISTRIBUTED_SYSTEM
changelog=0.2 Added an Operation selector with two new operations alongside spectral indices: PCA (false-colour PC composites) and Spectral Angle Mapper (SAM) target detection from a picked reference pixel, with optional detection mask and similarity band.
 0.1 Initial release: spectral indices (NDVI, NDWI, NDBI, SAVI, EVI, NDMI, MSAVI).
