Advanced Image Processing & GIS Integration

This capstone unit covers advanced image preprocessing, enhancement and filtering techniques (contrast enhancement, BCET, FFT-selective/adaptive filtering, fringe smoothing) together with statistical band selection and DDS theory. It also integrates GIS topics: handling vector/raster data conversion, automating GIS workflows, and addressing uncertainty and multi-criteria combination methods for reproducible remote sensing analyses.

Learning Objectives

• Analyze the effects of contrast enhancement methods (BCET, clipping, interactive techniques) and standardization/logarithmic-residual transforms on multispectral image statistics and spectral fidelity using quantitative metrics
• Apply FFT-selective, adaptive and fringe-smoothing filters as well as statistical band-selection procedures to preprocess imagery and document resulting improvements in signal-to-noise and feature separability
• Demonstrate the mathematical properties and practical implementation of DDS-based methods and implement automated GIS workflows that convert between raster and vector models to support end-to-end remote sensing analyses
• Evaluate spatial-analysis uncertainty and design multi-criteria combination strategies that incorporate uncertainty estimates to produce defensible, reproducible GIS outputs