Remote sensing and digital image analysis

1. FDRE Technical and Vocational Training Institute
Bahir Dar Satellite Campus
Department of Surveying Technology
Course Name: Digital Image Analysis
Course Code: SURT
Target: 5th year Surveying Technology
Student
April 3, 2024
Bahir Dar, Ethiopia

2. Chapter 2
Digital Image Analysis
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3. Outline
- Basic definition of digital image analysis
- Image pre-processing (Radiometric Correction, Geometric
Correction, Subsetting, layer stacking, and mosaicking)
- Image enhancement,
- Contrast Manipulation
- Spatial Feature Manipulation
- Multi-Image Manipulation
- Image interpretation tasks
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4. Digital image analysis
• Digital image analysis refers to the manipulation of digital
images with the aid of a computer.
• Simple and widely used methods for enhancing digital images,
correcting errors, and generally improving image quality prior
to further visual interpretation or digital analysis
• The use of computers for digital processing and analysis began
in the 1960s with early studies of airborne multispectral
scanner data and digitized aerial photographs.
• The central idea behind digital image processing is quite
simple. One or more images are loaded into a computer.
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5. • The computer is programmed to perform calculations using an
equation, or series of equations, that take pixel values from the raw
image as input. In most cases, the output will be a new digital image
whose pixel values are the result of those calculations.
• This output image may be displayed or recorded in pictorial format
or may itself be further manipulated by additional software.
• The possible forms of digital image manipulation are seemingly
infinite. However, virtually all these procedures may be categorized
into one (or more) of the following seven broad types of computer-
assisted operations:
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6. Image pre-processing
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7. Noise Removal
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8. Radiometric Correction
• All remotely sensed imagery has radiometric errors.
• The process of correcting radiometric errors is key to the effective use of
the imagery.
• Failure to radiometrically correct the imagery means failure to control
unwanted variation,
• Radiometric errors can be grouped into three categories:
1) issues related to the sensor,
2) issues related to sun angle and topography, and
3) issues related to the atmosphere.
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• A notable example of a sensor issue is the
problem on Landsat 7.
• The gaps in the imagery make the image less
useful for many applications

10. Geometric Correction
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11. Subsetting layer stacking and mosaicking
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12. Image Enhancement
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14. 1. Contrast Streching
- The linear stretch would be applied to each pixel in the image
using the algorithm
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15. 15
Principle of contrast stretch enhancement

16. Class Exercise
Let the image levels present in the scene be (60 to 158). You are
asked to fill the range of display values (0 to 255).
If DN=80
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17. 2. Spatial filtering (Convolution)
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18. 3. Multi-Image Manipulation
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19. 19
Band ratio images derived from
land sat TM data (Higher ratio
values are displayed in brighter
image tones)

20. Lab Exercise 1:
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Lab Exercise: Perform band rationing Using Land Sat 8 image of lake
Tana basin

21. Lab Exercise 2: NDVI
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22. Resampling Pixel Size
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For Example: Resample the pixel seize of
layerstacked land sat 8 image 30m
resolution in to 60m resolution using
ERDAS IMAGINE.
Raster  Spatial  Resample pixel size

23. Resolution Merge
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For Example: Merge the resolution of
land sat 8 image, layerstacked
multispectral 30m resolution in to 15 m
resolution using band 8 (Pancromatic
band ) on ERDAS IMAGINE.
Raster  Pan sharpen  Resolution
Merge