[general]
name=PCA Band Selector
qgisMinimumVersion=3.0
qgisMaximumVersion=4.99
description=Analyze multiband raster using PCA to find the most unique and informative band combinations
version=1.0.1
author=Ballu Harish
email=harishmanjualson@gmail.com
about=PCA Band Selector performs Principal Component Analysis (PCA) on any multiband raster (Landsat, Sentinel, AVIRIS, etc.) to identify which bands carry the most unique spectral information. It recommends optimal 2, 3, and 4-band combinations for classification and visualization by maximizing information content and minimizing inter-band redundancy.

 Features:
 - Explained variance chart per Principal Component
 - PC Loadings matrix (color coded)
 - Band uniqueness scores ranked
 - Best 2/3/4-band combination recommendations
 - Inter-band correlation matrix
 - Auto memory management for large images
 - Export results as TXT report or CSV
 - Compatible with QGIS 3.x and QGIS 4.x (Qt5 and Qt6)

tracker=https://github.com/HariMSS-WebGIS/pca-band-selector/issues
repository=https://github.com/HariMSS-WebGIS/pca-band-selector
tags=raster, PCA, remote sensing, band selection, multiband, Landsat, Sentinel, classification, principal components analysis, spectral, hyperspectral
homepage=https://github.com/HariMSS-WebGIS/pca-band-selector
category=Raster
icon=icons/icon.png
experimental=False
deprecated=False
server=False
hasProcessingProvider=no
changelog=1.0.1 - Fixed code style issues (Flake8)
    1.0.0 - Initial public release
    - PCA analysis on any multiband raster
    - Auto memory management for large images
    - Band uniqueness scoring and combination recommendations
    - Compatible with QGIS 3.x and 4.x
