Image Processing and Analysis

On successful completion of this course you will be able to:

• Identify a wide-range of image processing techniques
• Explain the purpose of each process and the underlying mathematical principles
• Select appropriate image processing sequences to achieve predetermined objectives
• Operate and manage an image processing system
• Integrate image processing techniques into applications of remote sensing.

• The remote sensing process: data management and planning
• Physics of light: principles of recording the image, plant, soil and water spectral properties in the optical wavelengths, influence of plant structure, moisture content, phenology and growth cycle on reflectance patterns, effect of organic matter, mineral content, texture and moisture content on soil reflectance
• Satellite image processing: Digital image enhancement and classification, indices
• Geometric correction: map projections, selection of ground control points, transform equations, resampling methods (nearest neighbour, bilinear interpolation, cubic convolution, sinc x)
• Image enhancement: contrast stretching (linear, bilinear, gaussian, histogram equalisation and manual), digital filtering in the spatial domain (low-pass, high-pass, high-boost, median and directional)
• Classification: density slice, box classification, maximum likelihood and minimum distance algorithms. Supervised and unsupervised training techniques. Spectral coincident plots and decision tree classification
• Advanced image processing techniques: principal component analysis and formation of eigen images. Band arithmetic. Masking. De-correlation stretch
• Current classification methods.