Introduction To Image Processing-lab Report
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SGS 1633 REMOTE SENSING TECHNOLOGY 1
LAB REPORT 1
LECTURER : PROF MOHD IBRAHIM SEENI MOHD
PREPARED BY: MOHD FARID BIN FAUZI 900707-03-5463 AG090090 1-SGS 2009/10
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
10 20
TITLE Introduction to Image Processing OBJECTIVES 2.1 To enhance the satellite data by using combination of different
band. 2.2 To observe and differentiate on the image displayed by using
different band and determine what the band good for. 2.3 Analysing data from the image data in graphical form and
description form. 2.4Make a conclusion for the best combination of band for better image result. 10
METHODOLOGY 3.1 By using Geomatica v9.1 software, display the image data for
studied place. 3.2 For Task 1,use same band for all three color wavelength; red,green
Page
and blue. 3.3Make enhancement for clear image and observe what part on the picture that appearing clearly. 3.4Conclude what the function of each band and compare it with text book. 3.5Then, find the best combination of RGB wavelength in order to get best and clear image. 3.6 For Task 2,take the Digital Number(DN) data from six or seven difference places for each bands. The digital numbers are acquisited using the same software. 3.7Find the average Digital Number(DN) for each point or place and tabulate the data in the table form. 3.8Afterwards, plot the band(wavelength) versus Digital Number(DN) graph. 3.9An analysis of this experiment/practical work is written properly.
2 Page |2
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
10
RESULT Task 1 Band 1 2 3 4 5 6 7
Type of enhancement Linear Linear Root Root Root Equalization Adaptive
Details which appearing clearly Urban area Open area Road/Highway Water Mangrove Thermal Vegetation
The best combination found was R-7, G-5 and B-2 with adaptive enhancement technique. This combination will basically show the different between vegetation area, water surface, urban area, open area, road and more. It let the observer differentiate these areas easily. We also can use the combination of R-7, G-5 and B-2 as it also produces better image which we can defined the different type of areas. Task 2 Digital Number of Each Band Band 3
Band 4
Band 5
Band 7
Band 6
84.71 89.00 87.20 98.68 109.67 145.04 119.19
34.78 40.45 33.64 45.18 52.04 91.43 80.27
37.76 50.41 36.27 52.98 73.14 167.41 147.58
103.34 75.51 21.41 44.64 59.33 127.51 114.02
68.80 96.27 19.11 35.95 110.16 218.76 208.63
19.02 34.76 8.95 14.72 52.08 89.51 77.3
117.02 119.78 116.90 109.91 125.02 115.31 120.32
Page |3
3
Band 2
Page
Vegetation 1 Vegetation 2 Sediment Water Dark Water Urban Area Open Area Other
Band 1
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
20
ANALYSING DATA
Task 1 Band 1 • • • •
The wavelength of this band is between 0.45µm to 0.52µm,blue in colour. Increased penetration of water bodies is provided by this band. This band have shorter wavelength than the other bands. Its sensitivity is 0.8
Band 2 • • • •
The wavelength of this band is between 0.52µm to 0.62µm,green in colour. It spans the region between the blue and red chlorophyll absorption bands. This band is correspond to the green reflectance of wealthy vegetation. Its sensitivity is 0.5
Band 3 • • • •
The wavelength of this band is between 0.63µm to 0.69µm,red in colour. This is red chlorophyll absorption band. Band 3 is useful for soil boundary and geological-boundary delineation. Its sensitivity is 0.5 Page
Band 4
• • •
The wavelength of this band is 0.76µm to 0.90µm,reflective infrared band. Its responsive to the amount of vegetation biomass present in ascene. This band is good for crop identification and emphasizes soil/crop and land/water contrast. Its sensitivity is 0.5
Page |4
4
•
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
Band 5 • • • • •
The wavelength of this band is 1.55µm to 1.75µm,mid infrared band. It is sensitive to the turgidity or amount of water in plants. This band is very important in hydrologyc researh. This can discriminated between clouds,show and ice. Its sensitivity is 0.5
Band 6 • The wavelength of this band is 10.4µm to 12.5µm.This is thermal infrared band. • This band is good for measures the amount of infrared radiant flux emitted from surfaces. • It is useful for locating geothermal activity.It can do thermal inetity,mapping for geologic investigation,vegetation classification,vegetation stress analysis and soil moisture studies. Band 7 • The wavelength of this band is 2.08µm to 2.35µm,mid infrared band. • This band is important for the discrimination of geologic rock formation. • It is shown to be particularly effective in identifying zone of hydrothermals alternations in rocks.
Page
5 Page |5
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
Task 2
OPEN AREA
OTHER AREA
VEGETATION 1 URBAN AREA
VEGETATION 2
DARK WATER SEDIMENT WATER
Page
6 Page |6
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
THE GRAPH ANALYSIS • • • • • • • •
5.1
The entire graph fluctuating in increase of wavelength. From visible light wavelength to infrared wavelength, most of the graph decrease in Digital Number. At band 6, the digital number of all place studies almost (nearly) the same. We cannot use band 6 (thermal band) in define the differences between area spatial resolution. Watery place have lowest digital number due to high absorption. Open area reflect more EMR and shows higher digital number. The difference between sediment water and vegetation 1 is hard to determine in band 1 to band 3 because of the absorption of EMR is almost the same. The Digital Number in band 7 is lower than band 6 is because more EMR trapped by particle and cloud at the atmosphere. Band 6 (infrared) which has longer wavelength can penetrate the cloudy area. THEORETICALLY DATA
Page
7 Page |7
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
In reflected-light spectroscopy the fundamental property that we want to obtain is spectral reflectance: the ratio of reflected energy to incident energy as a function of wavelength. Reflectance varies with wavelength for most materials because energy at certain wavelengths is scattered or absorbed to different degrees. These reflectance variations are evident when we compare spectral reflectance curves (plots of reflectance versus wavelength) for different materials, as in the illustration below. Pronounced downward deflections of the spectral curves mark the wavelength ranges for which the material selectively absorbs the incident energy. These features are commonly called absorption bands (not to be confused with the separate image bands in a multispectral or hyperspectral image). The overall shape of a spectral curve and the position and strength of absorption bands in many cases can be used to identify and discriminate different materials. For example, vegetation has higher reflectance in the near infrared range and lower reflectance of red light than soils. Representative spectral reflectance curves for several common Earth surface materials over the visible light to reflected infrared spectral range. The spectral bands used in several multispectral satellite remote sensors are shown at the top for comparison. Reflectance is a unitless quantity that ranges in value from 0 to 1.0, or it can be expressed as a percentage, as in this graph. When spectral measurements of a test material are made in the field or laboratory, values of incident energy are also required to calculate the materials reflectance. These values are either measured directly or derived from measurements of light reflected (under the same illumination conditions as the test material) from a standard reference material with known spectral reflectance. Source: http://www.microimages.com/getstart/pdf/hyprspec.pdf
Page |8
8
RESULT 1.1 Every band (wavelength) has different function in image processing. 1.2 We need to consider each band in defining the object or area studied. 1.3 We can see image clearly by making enhancement. 1.4 Watery surface has lower digital number than other surface. 1.5 Thermal band is not suitable for spatial resolution. 1.6 Combination of RGB can give better image which can show different physical geography clearly and easily.
Page
10
LAB REPORT 1
LECTURER : PROF MOHD IBRAHIM SEENI MOHD
PREPARED BY: MOHD FARID BIN FAUZI 900707-03-5463 AG090090 1-SGS 2009/10
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
10 20
TITLE Introduction to Image Processing OBJECTIVES 2.1 To enhance the satellite data by using combination of different
band. 2.2 To observe and differentiate on the image displayed by using
different band and determine what the band good for. 2.3 Analysing data from the image data in graphical form and
description form. 2.4Make a conclusion for the best combination of band for better image result. 10
METHODOLOGY 3.1 By using Geomatica v9.1 software, display the image data for
studied place. 3.2 For Task 1,use same band for all three color wavelength; red,green
Page
and blue. 3.3Make enhancement for clear image and observe what part on the picture that appearing clearly. 3.4Conclude what the function of each band and compare it with text book. 3.5Then, find the best combination of RGB wavelength in order to get best and clear image. 3.6 For Task 2,take the Digital Number(DN) data from six or seven difference places for each bands. The digital numbers are acquisited using the same software. 3.7Find the average Digital Number(DN) for each point or place and tabulate the data in the table form. 3.8Afterwards, plot the band(wavelength) versus Digital Number(DN) graph. 3.9An analysis of this experiment/practical work is written properly.
2 Page |2
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
10
RESULT Task 1 Band 1 2 3 4 5 6 7
Type of enhancement Linear Linear Root Root Root Equalization Adaptive
Details which appearing clearly Urban area Open area Road/Highway Water Mangrove Thermal Vegetation
The best combination found was R-7, G-5 and B-2 with adaptive enhancement technique. This combination will basically show the different between vegetation area, water surface, urban area, open area, road and more. It let the observer differentiate these areas easily. We also can use the combination of R-7, G-5 and B-2 as it also produces better image which we can defined the different type of areas. Task 2 Digital Number of Each Band Band 3
Band 4
Band 5
Band 7
Band 6
84.71 89.00 87.20 98.68 109.67 145.04 119.19
34.78 40.45 33.64 45.18 52.04 91.43 80.27
37.76 50.41 36.27 52.98 73.14 167.41 147.58
103.34 75.51 21.41 44.64 59.33 127.51 114.02
68.80 96.27 19.11 35.95 110.16 218.76 208.63
19.02 34.76 8.95 14.72 52.08 89.51 77.3
117.02 119.78 116.90 109.91 125.02 115.31 120.32
Page |3
3
Band 2
Page
Vegetation 1 Vegetation 2 Sediment Water Dark Water Urban Area Open Area Other
Band 1
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
20
ANALYSING DATA
Task 1 Band 1 • • • •
The wavelength of this band is between 0.45µm to 0.52µm,blue in colour. Increased penetration of water bodies is provided by this band. This band have shorter wavelength than the other bands. Its sensitivity is 0.8
Band 2 • • • •
The wavelength of this band is between 0.52µm to 0.62µm,green in colour. It spans the region between the blue and red chlorophyll absorption bands. This band is correspond to the green reflectance of wealthy vegetation. Its sensitivity is 0.5
Band 3 • • • •
The wavelength of this band is between 0.63µm to 0.69µm,red in colour. This is red chlorophyll absorption band. Band 3 is useful for soil boundary and geological-boundary delineation. Its sensitivity is 0.5 Page
Band 4
• • •
The wavelength of this band is 0.76µm to 0.90µm,reflective infrared band. Its responsive to the amount of vegetation biomass present in ascene. This band is good for crop identification and emphasizes soil/crop and land/water contrast. Its sensitivity is 0.5
Page |4
4
•
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
Band 5 • • • • •
The wavelength of this band is 1.55µm to 1.75µm,mid infrared band. It is sensitive to the turgidity or amount of water in plants. This band is very important in hydrologyc researh. This can discriminated between clouds,show and ice. Its sensitivity is 0.5
Band 6 • The wavelength of this band is 10.4µm to 12.5µm.This is thermal infrared band. • This band is good for measures the amount of infrared radiant flux emitted from surfaces. • It is useful for locating geothermal activity.It can do thermal inetity,mapping for geologic investigation,vegetation classification,vegetation stress analysis and soil moisture studies. Band 7 • The wavelength of this band is 2.08µm to 2.35µm,mid infrared band. • This band is important for the discrimination of geologic rock formation. • It is shown to be particularly effective in identifying zone of hydrothermals alternations in rocks.
Page
5 Page |5
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
Task 2
OPEN AREA
OTHER AREA
VEGETATION 1 URBAN AREA
VEGETATION 2
DARK WATER SEDIMENT WATER
Page
6 Page |6
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
THE GRAPH ANALYSIS • • • • • • • •
5.1
The entire graph fluctuating in increase of wavelength. From visible light wavelength to infrared wavelength, most of the graph decrease in Digital Number. At band 6, the digital number of all place studies almost (nearly) the same. We cannot use band 6 (thermal band) in define the differences between area spatial resolution. Watery place have lowest digital number due to high absorption. Open area reflect more EMR and shows higher digital number. The difference between sediment water and vegetation 1 is hard to determine in band 1 to band 3 because of the absorption of EMR is almost the same. The Digital Number in band 7 is lower than band 6 is because more EMR trapped by particle and cloud at the atmosphere. Band 6 (infrared) which has longer wavelength can penetrate the cloudy area. THEORETICALLY DATA
Page
7 Page |7
August 5, [INTRODUCTION TO IMAGE PROCESSING] 2009
In reflected-light spectroscopy the fundamental property that we want to obtain is spectral reflectance: the ratio of reflected energy to incident energy as a function of wavelength. Reflectance varies with wavelength for most materials because energy at certain wavelengths is scattered or absorbed to different degrees. These reflectance variations are evident when we compare spectral reflectance curves (plots of reflectance versus wavelength) for different materials, as in the illustration below. Pronounced downward deflections of the spectral curves mark the wavelength ranges for which the material selectively absorbs the incident energy. These features are commonly called absorption bands (not to be confused with the separate image bands in a multispectral or hyperspectral image). The overall shape of a spectral curve and the position and strength of absorption bands in many cases can be used to identify and discriminate different materials. For example, vegetation has higher reflectance in the near infrared range and lower reflectance of red light than soils. Representative spectral reflectance curves for several common Earth surface materials over the visible light to reflected infrared spectral range. The spectral bands used in several multispectral satellite remote sensors are shown at the top for comparison. Reflectance is a unitless quantity that ranges in value from 0 to 1.0, or it can be expressed as a percentage, as in this graph. When spectral measurements of a test material are made in the field or laboratory, values of incident energy are also required to calculate the materials reflectance. These values are either measured directly or derived from measurements of light reflected (under the same illumination conditions as the test material) from a standard reference material with known spectral reflectance. Source: http://www.microimages.com/getstart/pdf/hyprspec.pdf
Page |8
8
RESULT 1.1 Every band (wavelength) has different function in image processing. 1.2 We need to consider each band in defining the object or area studied. 1.3 We can see image clearly by making enhancement. 1.4 Watery surface has lower digital number than other surface. 1.5 Thermal band is not suitable for spatial resolution. 1.6 Combination of RGB can give better image which can show different physical geography clearly and easily.
Page
10
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