ge 1 rs03 basic digital image processing
TRANSCRIPT
![Page 1: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/1.jpg)
Basic
Digital Image Processing
Wilfredo M. Rada
Assistant Professor
University of the Philippines
![Page 2: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/2.jpg)
Outline
I. Digital Image
II. Characteristics of a Digital Image
III. Multilayer Image
IV. Visualization
V. Three Broad Categories of Image Processing
VI. Preprocessing
VII. Contrast Enhancement
VIII.Spatial Filtering
IX. Density Slice
2
![Page 3: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/3.jpg)
3
Digital Image
Digital image is a two-
dimensional array of pixels.
Each pixel has an
intensity value
(represented by a digital number)
and a
location address
(referenced by its row and column
numbers).
![Page 4: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/4.jpg)
4
Sample Digital Image
![Page 5: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/5.jpg)
5
![Page 6: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/6.jpg)
6
Characteristics of a Digital Image
1. Spatial Resolution
2. Spectral Resolution
3. Radiometric Resolution
4. Temporal Resolution
![Page 7: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/7.jpg)
7
Spatial Resolution
Pixel Size = 10 m
Image Width = 160 pixels
Height = 160 pixels
Pixel Size = 20 m
Image Width = 80 pixels
Height = 80 pixels
• Spatial Resolution refers to the size of the smallest
object that can be resolved on the ground.
• In a digital image, the resolution is limited by the pixel size.
![Page 8: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/8.jpg)
8
Spatial Resolution
Pixel Size = 40 m
Image Width = 40 pixels
Height = 40 pixels
Pixel Size = 80 m
Image Width = 20 pixels
Height = 20 pixels
![Page 9: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/9.jpg)
9
Visual Effect of Spatial Resolution
![Page 10: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/10.jpg)
10
Spectral Resolution
Spectral Resolution refers to the specific wavelength
intervals in the electromagnetic spectrum that a
sensor can record.
Pan: 450 - 900 nm
QuickBird Blue: 450 - 520 nm
Green: 520 - 600 nm
Image Bands Red: 630 - 690 nm
Near IR 760 - 900 nm
Pan: 480 - 710 nm
SPOT-5 Green: 500 - 590 nm
Red: 610 - 680 nm
Image Bands Near IR: 780 – 890 nm
ShortWave IR: 1,580 – 1,750 nm
![Page 11: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/11.jpg)
11
Radiometric Resolution
8-bit quantization
(256 levels)
6-bit quantization
(64 levels)
• Radiometric Resolution refers to the smallest change in
intensity level that can be detected by the sensing system.
• In a digital image, the radiometric resolution is limited by the
number of discrete quantization levels used to digitize the
continuous intensity value.
![Page 12: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/12.jpg)
12
2-bit quantization
(4 levels)
1-bit quantization
(2 levels)
4-bit quantization
(16 levels)
3-bit quantization
(8 levels)
![Page 13: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/13.jpg)
13
Gray Scale
[256 level gray scale]
Most raw unprocessed satellite
imagery is stored in a gray scale
format.
A gray scale is a color scale that
ranges from black to white, with
varying intermediate shades of
gray.
A commonly used gray scale for
remote sensing image processing
is a 256 shade gray scale, where a
value of 0 represents a pure black
color, the value of 255 represents
pure white, and each value in
between represents a progressively
darker shade of gray.
![Page 14: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/14.jpg)
14
Temporal Resolution
Temporal Resolution relates to the repeat cycle or interval between successive acquisitions.
Examples:
Landsat-7 Revisit Time: 15 days
SPOT-5 Revisit Time: 2-3 days depending on Latitude
IKONOS Revisit Time: Approximately 3 days at 40° latitude
QuickBird Revisit Time: 1-3.5 days depending on Latitude
(30º off-nadir)
![Page 15: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/15.jpg)
15
Multilayer Image
Multilayer image is formed by "stacking"
images from the same area together.
Each component image is a layer in the
multilayer image and carry some specific
information about the area.
Multilayer images can also be formed by
combining images obtained from different
sensors, and other subsidiary data.
![Page 16: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/16.jpg)
16
Multilayer Image
An illustration of a multilayer image consisting of five component layers.
![Page 17: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/17.jpg)
17
Visualization
SUBTRACTIVE PRIMARY COLORS
![Page 18: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/18.jpg)
18
Additive Color Display
Green + Blue
= Cyan
Red + Green
= Yellow
Red + Blue
= Magenta
Red + Green
+ Blue
= White
![Page 19: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/19.jpg)
19
RGB Band Composite
![Page 20: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/20.jpg)
20
Sample Landsat TM Composite Images BAND 1
BAND 2
BAND 4 BAND 6
BAND 3
BAND 5
BAND 7
RGB 741 RGB 572
RGB 432 RGB 543
![Page 21: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/21.jpg)
21
Certain bands or band combinations are better than others for identifying specific land cover features.
Landsat TM Red= band 3, Green = band 2, Blue = band 1
Landsat TM Red= band 4, Green = band 5, Blue = band 3
![Page 22: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/22.jpg)
22
Three Broad Categories
of Image Processing
Image Restoration (Preprocessing)
Image Enhancement
Classification and Information Extraction
![Page 23: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/23.jpg)
23
Digital Image Processing Flow
![Page 24: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/24.jpg)
24
Preprocessing
Preprocessing is an important and diverse set of image preparation programs that act to offset problems with the band data and recalculate DN values that minimize these problems.
![Page 25: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/25.jpg)
Among the radiometric and geometric
corrections are:
• atmospheric correction
• sun illumination geometry
• surface-induced geometric distortions
• spacecraft velocity and attitude variations (roll, pitch, and yaw)
• effects of Earth rotation, elevation, curvature (including skew effects),
• abnormalities of instrument performance
• loss of specific scan lines (requires destriping), and others
25
![Page 26: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/26.jpg)
26
Sample Geometric Distortions
![Page 27: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/27.jpg)
27
Sample Geometric Distortions
![Page 28: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/28.jpg)
28
Sun Illumination Geometry
![Page 29: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/29.jpg)
29
Contrast Enhancement
It is an image processing procedure that improves
the contrast ratio of images.
The original narrow range of digital values is
expanded to utilize the full range of available digital
values.
It is useful to examine the image histograms before
performing any image enhancement
![Page 30: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/30.jpg)
30
Sample Image Histograms
![Page 31: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/31.jpg)
31
Sample Contrast Enhancement Methods
![Page 32: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/32.jpg)
32
Image & Histogram
![Page 33: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/33.jpg)
33
Image & Histogram
![Page 34: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/34.jpg)
34
Sample Enhanced Images
![Page 35: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/35.jpg)
35
Spatial Filtering
Spatial filtering explores the distribution of pixels of varying brightness over an image and, especially detects and sharpens boundary discontinuities.
These changes in scene illumination, which are typically gradual rather than abrupt, produce a relation that we express quantitatively as "spatial frequencies".
![Page 36: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/36.jpg)
Spatial Filtering
Filters that pass high frequencies and, hence, emphasize fine detail and edges, are called highpass filters.
Lowpass filters, which suppress high frequencies, are useful in smoothing an image, and may reduce or eliminate "salt and pepper" noise.
36
![Page 37: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/37.jpg)
37
Sample Filtered Images
high pass filter
image
low pass filter
image
contrast-stretched
image
image from
a large
convolution
window
![Page 38: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/38.jpg)
38
Smoothing Vs Sharpening
![Page 39: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/39.jpg)
39
Ratioing
Ratioing is an enhancement process in which the DN value of one band is divided by that of any other band in the sensor array.
Image ratioing is commonly used in vegetation studies.
The most widely used measure is a normalized difference vegetation index (NDVI) which is calculated by taking the difference in brighness values between the near IR and the red bands and dividing that difference by the sum of the same two bands.
![Page 40: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/40.jpg)
Sample NDVI Formula
For example, using Thematic mapper data, band 4 is the near IR and band 3 is red:
NDVI = (TM4 - TM3) / (TM4 + TM3)
40
![Page 41: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/41.jpg)
41
Sample NDVI Image
![Page 42: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/42.jpg)
42
Density Slice
Density Slice is a straightforward form of
enhancement that results from the combining
("lumping together") of DNs of different values within
a specified range or interval into a single value.
It is also called "level slice" method and works best
on single band images. It is especially useful when a
given surface feature has a unique and generally
narrow set of DN values.
![Page 43: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/43.jpg)
43
Sample Density Sliced Images
This map has four levels
or slices. The lavender
tends to demarcate a gray
level (DN 43 to 48) that
associates with urban
areas.
![Page 44: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/44.jpg)
44
Six gray levels (each
representing a DN range)
have been colorized as
follows:
Black = (DN) 0-19;
Blue = 20-34;
Red = 35-44; White = 45-54;
Brown = 55-69; Green = 70+
The black pattern is almost entirely tied to water; the blue denotes
heavily built up areas; the green marks vegetation; the other colors
indicate varying degrees of suburbanization and probably some open
areas.
Sample Density Sliced Images
![Page 45: Ge 1 rs03 basic digital image processing](https://reader033.vdocuments.site/reader033/viewer/2022052619/555b9b9ad8b42a6e588b4817/html5/thumbnails/45.jpg)
45