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Image Processing and Analysis

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Digital Image Processing for Environmental Remote
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Cranfield University
School of Applied Sciences
Contact Provider
Short Course
Cranfield University, Cranfield, MK43 0AL, Bedfordshire, United Kingdom

5 day course

Course overview

This course aims to develop knowledge of image processing techniques to select appropriate processing techniques for images from a wide range of sources.

This course is suitable for delegates wishing to gain a basic level of competence in the operation of the Erdas Imagine image processing package.

Course description

    • Introduction: role of image processing methods
    • Image restoration and display: digital representation of imagery by scanners, spatial resolution, pixels, spectral resolution, digital format of images.
    • RGB and IHS colour space representations
    • Corrections for scanner malfunctions
    • 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)
    • Geometric correction: map projections, selection of ground control points, transform equations, resampling methods (nearest neighbour, bilinear interpolation, cubic convolution, sinc x)
    • Digital mosaicing
    • 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
    • Selection of appropriate image processing system and planning digital processing sequences
    • Current classification methods

    On completion of this course the delegate will be able to:

    1. identify a wide range of image processing techniques
    2. explain the purpose of each process and the underlying mathematical principles
    3. select appropriate image processing sequences to achieve predetermined objectives
    4. operate and manage an image processing system
    5. Integrate image processing techniques into applications of remote sensing

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