ImageQualityToolset
Computes MTF and SNR image quality metrics from satellite imagery using Knife Edge, Bridge (Pulse), and Variogram methods.
The Image Quality Toolset is a QGIS plugin developed in the context of the ESA AI4QC project. It targets remote sensing Calibration/Validation users as a supporting tool for Quality Control (QC) of satellite imagery.
It integrates into the QGIS Processing Toolbox and provides a command-line interface to perform image quality assessments from Regions of Interest (ROIs) defined on an input raster. ROIs are processed to derive Modulation Transfer Function (MTF) and Signal-to-Noise Ratio (SNR) image quality measures. Results are exported as diagnostic PNG figures and cumulative GeoPackage reports.
Three methods are available:
- MTF Knife Edge Method: estimates MTF from a sharp contrast transition between two uniform areas. Derived metrics include MTF@Nyquist, MTF30, MTF50, FWHM, RER, HEE, and R².
- MTF Bridge (Pulse) Method: estimates MTF from a narrow pulse target (bridge structure).
- SNR Variogram Method: computes SNR by combining a Histogram method and a Variogram method, with per-pixel local SNR estimation.
Each method requires an input raster and a polygon ROI (shapefile). Radiometric scale and offset parameters allow conversion from raw DN to radiance. Results are accumulated across runs in a GeoPackage report, one feature per analysis, with full metadata and geometry.
The plugin uses a dual-license model: the QGIS integration layer is released under GPL v3; the core signal-processing algorithms (MTF, SNR, ESF models, variogram) are released under Apache 2.0.