Foundations of Remote Sensing Image Processing

This unit introduces core concepts and practical techniques for digital image representation, visualization, and basic processing used in remote sensing. Students learn histogram and contrast adjustments, image arithmetic, spatial and frequency-domain filtering, color-space transforms and data-fusion methods, plus fundamentals of geometric registration, sensor types, and available software and data resources to prepare imagery for GIS analysis.

Learning Objectives

• Analyze digital image characteristics (pixel value ranges, bit depth, histograms) and apply histogram modification, lookup tables, and linear contrast enhancement to optimize image display
• Apply image arithmetic and change-detection operations (addition, subtraction/differencing) and implement spatial and frequency-domain filtering (convolution, Fourier filtering) to enhance or suppress image features
• Demonstrate color-coordinate transformations, RGB–IHS fusion, and principal component analysis to integrate multispectral data and improve thematic information extraction
• Evaluate geometric deformation and registration approaches, including phase correlation and sensor-specific considerations, and select appropriate software and data sources to prepare imagery for subsequent GIS and classification workflows