1. Image Processing
MR1510
Lecture 5

2. Image Processing Data Information Pathway Definition
Image Processing is defined as the "examination, processing and analysis of (remotely sensed) images for the purpose of identifying objects and extracting information"
Image analysts study remotely sensed data and use visual and computer-based processing techniques, tools and equipment to detect, identify, classify, measure and evaluate physical and cultural objects (the environment), their spatial patterns and relationships
Data Information Pathway

3. Image Processing
Images are available in two forms - photographic film form and digital form.
Aerial Photographs (oblique and vertical) – taken with a camera/film/filter combination are considered to be traditional forms of remotely sensed imagery – known as ANALOG format
Analysed and Interpreted using Photo-interpretation (mirror and pocket stereoscopes)
Variations in the scene characteristics are represented as variations in brightness on photographic films. A particular part of scene reflecting more energy will appear bright while a different part of the same scene that reflecting less energy will appear black.
Today, most remotely sensed imagery (as opposed to photography) is recorded in a DIGITAL format for processing by desktop computers (PCs) to produce computer-based images for (online) interpretation purposes.

4. Image Processing
128
128
255
Digital images consist of discrete picture elements called PIXELS. Associated with each pixel is a number represented as DN (Digital Number), that depicts the average radiance of relatively small area within a scene. The size of this area affects the reproduction of details within the scene. As the pixel size is reduced more scene detail is preserved in digital representation (spatial resolution). DN
255
128
PIXEL
PIXEL
255
Matrix of Numbers

5. Image Processing
Analysis of remotely sensed data is undertaken using various image processing techniques and tools including:
Analog image processing. (traditional)
Digital image processing. (computer)
Visual or Analog processing techniques are applied to hard copy data/and softcopy or on-screen such as photographs or printouts, computer displays. Image analysis in visual techniques adopts certain elements of interpretation, which are as follows:
Tone, Texture, Colour, Shape, Size, Association….
The use of these fundamental elements depends not only on the area being studied, but the knowledge the analyst has of the study area. For example the texture of an object is also very useful in distinguishing objects that may appear the same if the judging solely on tone (i.e., water and a tree canopy, may have the same mean brightness values, but their texture is much different).

6. Aerial Photography Characteristics 9” (23cm) 9” (23cm)
Bubble Level
Film Type and Focal length
of lens
Clock
Mask
Altimeter
(height)
9” (23cm)
Principal Point (PP)
Fiducial Marks
9” (23cm)
Documentation

7. Aerial Photography Stereoscopy Aircraft Flightline 2D plane
40% gain
60% overlap
Stereocover (Geonex software – Photogrammetric Flight Planner)
Stereoscopic viewing
Pocket stereoscope
Mirror stereoscope
Stereoscopic pair
Baselining
Eyebase (distance between photo frames)
Viewing
3D model
Magnification – Exaggeration
Aid to mapping
Photogrammetry (quantitative measurements from photographs including heighting/contouring)
Height (topography)
3D world
Ground
Sea level

8. Image Processing
Association, for example, is a very powerful image analysis tool when combined with general knowledge (apriori) of the site.
Collateral, Contextual or Ancillary data and personal knowledge of the task assist in image processing.
The combination of examining remotely sensed data in the form of multispectral, multitemporal, multiscale imagery, in conjunction with multidisciplinary approaches provide us with a clue to identity of a feature
Analog image processing techniques also include optical photogrammetric techniques (photgrammetry) allowing for precise measurement of the height, width, location, etc. of an object.

9. Digital Image Processing
Digital Image Processing is a collection of techniques for the manipulation of digital images by computers. Raw data received from sensors on the satellite platforms contains flaws and deficiencies.
To overcome these flaws and deficiencies in order to get the original data several steps of processing are required.
This varies from image to image depending on the type of image format, initial condition of the image and the information of interest and the composition of the image scene.
Pre-processing
Feature Extraction
Display and enhancement
Information extraction 1 2 3 1 4 2 3 4

10. Digital Image Processing
Pre-processing prepares image data for subsequent analysis and attempts to correct or compensate for systematic errors present in all images.
The digital images are corrected for geometry and atmospheric noise (amongst other things),
These errors are systematic and can be removed before they reach the user.

11. Digital Image Processing
Geometric Corrections
Raw digital images often contain serious geometrical distortions that arise from Earth curvature, platform motion, relief displacement of the ground, scanning device. The distortions involved are of two types:
Non-systematic Distortion
Systematic Distortions
Rectification is the process of projecting image data onto a plane or surface and making it conform to a map projection system.
Registration is the process of making image data conform to another image. A map coordinate system is not necessarily involved.
Rectification involves rearrangement of the input pixels onto a new grid which conforms to the desired map projection and coordinate system.
Rectification and Registration therefore involve similar sets of procedures for both the distortions.

12. Digital Image Processing
Atmospheric Corrections
The output from the instrument on satellite (the image) depends on the intensity and spectral distribution of energy that is received at the satellite.
The intensity and spectral distribution of energy/radiation travels through the atmosphere and accordingly suffers both attenuation (reduction) and augmentation (addition) in the course of journey.
A problem for interpretation concerns not being able to regenerate the correct radiation properties of the target body (at the ground) on the Earth’s surface with the data generated by the remote sensing
Restore ‘image’

13. Digital Image Processing
Feature Extraction
“Statistical" characteristics of image data such as individual bands or a combination of band values that carry information concerning systematic variation within the scene.
In a multi-spectral dataset it helps to portray the necessary elements of the image.
It reduces the number of spectral bands that have to be analyzed.
Finally it leads to increases in the speed of analysis and reduces the cost of analysis.

14. Digital Image Processing
Image Enhancement Techniques Image Enhancement techniques are used to make satellite (as opposed to aerial photography) imagery more informative and to help achieve the goal of image interpretation.
Enhancement means alteration of the appearance of an image in such a way that the information contained in that image is more readily interpreted visually in terms of a particular need.
The image enhancement techniques are applied either to single-band images or separately to the individual bands of a multi-band image set. These techniques can be categorized into two:
Spectral Enhancement Techniques
Multi-Spectral Enhancement Techniques

15. Digital Image Processing
Image Enhancement serves to improve the interpretability of the image by increasing apparent contrast among various features in the scene.
The enhancement techniques depends upon two factors:
The digital data (i.e. with spectral bands and resolution)
The objectives of the interpretation
As an image enhancement technique often drastically alters the original numeric data, it is normally used only for visual (manual) interpretation and not for further numeric analysis.

16. Image Enhancement ? MAT (i,j) - n x n FILTMAT (i,j) - 3 x 3 Column (j)
e.g. FILTERING
FILTMAT (i,j) - 3 x 3
Column (j)
Column (j)
124
255 23
200 12
128 25
100
245 1 ?
Row (i)
Row (i) ?

17. Digital Image Processing
Information Extraction is the final step in image analysis.
After pre-processing, feature extraction, and image enhancement the remotely sensed data is subjected to quantitative analysis to assign individual pixels to specific classes.
Classification of the image is based on the known and unknown identity to classify the remainder of the image consisting of those pixels of unknown identity.
After classification is complete, it is necessary to evaluate its accuracy by comparing the categories on the classified images with the areas of known identity on the ground (ground-truthing)
The final result of the analysis consists of a map (or image)

18. Digital Image Processing
Typical Examples of Digital Image Processing software:
Erdas Imagine (UoA) – Geography folder
Idrisi Kilimanjaro (UoA) – Geography folder
Multispec (free download)
PCI Geomatics
ERMapper
ENVI
Pixoneer PGSteamer
Also training package from UNESCO ….. BILKO

19. Digital Image Processing

20. Digital Image Processing
BILKO EXERCISES (DULY COMPLETED)
Introduction to Digital Image Processing
Applications x 2
Read instructions. Introduction familiarises you with the software (BILKO) and the two applications allow you to carry out a couple of simple exercises using the software
Available on the website
Further details about BILKO at: