CA2491794A1 - Method for generating natural colour satellite images - Google Patents
Method for generating natural colour satellite images Download PDFInfo
- Publication number
- CA2491794A1 CA2491794A1 CA 2491794 CA2491794A CA2491794A1 CA 2491794 A1 CA2491794 A1 CA 2491794A1 CA 2491794 CA2491794 CA 2491794 CA 2491794 A CA2491794 A CA 2491794A CA 2491794 A1 CA2491794 A1 CA 2491794A1
- Authority
- CA
- Canada
- Prior art keywords
- band
- pan
- greenness
- sharpened
- orig
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Abstract
A simple and effective method is disclosed in the present invention to adjust the near natural colour of a satellite colour composite to a visually more pleasing natural colour. This method includes two steps: (1) extracting vegetation "greenness"
from available multispectral bands, and (2) adding (injecting) the "greenness" into the vegetation areas of the green band being displayed.
from available multispectral bands, and (2) adding (injecting) the "greenness" into the vegetation areas of the green band being displayed.
Description
METHOD FOR GENERATING NATURAL COLOUR SATELLITE IMAGES
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority from United States Patent application serial no.
10/ 756,781 filed January 14, 2004.
FIELD OF THE INVENTION
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority from United States Patent application serial no.
10/ 756,781 filed January 14, 2004.
FIELD OF THE INVENTION
[0002] This invention relates to the field of image processing and in particular a method of generating natural colour satellite images.
BACKGROUND OF THE INVENTION
BACKGROUND OF THE INVENTION
[0003] Generally, the blue, green and red bands of multispectral satellite sensors do not cover the whole blue, green and red wavelength ranges, respectively. As a result, the "natural" colour composites from the blue, green and red bands do not reproduce natural colours as found in the nature or on a colour photo. Such colour is near natural colour, but still noticeably unnatural. In order to achieve a better visual effect, it is useful to adjust, either manually or automatically, the near natural colour to a more natural colour. Such a colour adjustment is useful in many applications, such as colour image mapping, GIS integration, image visualization, and other purposes.
[0004] The most representative ground covers on the Earth's surface are vegetation, water and soil (e.g., surface not covered by vegetation or water). Their general spectral reflectance in different spectral ranges is characterized in Figure 1.
Vegetation curves have a peak in the green range compared to the blue and red ranges. The spectral curves of soil reflectance rise proportional to the wavelength. However, the curve of clear water usually has a peak in blue range and then descends proportional to the wavelength. Therefore, when the blue, green and red bands of a multispectral sensor are displayed with blue, green and red colour, a near natural colour composite can be generated with water shown in blue, vegetation shown in green and soil shown in light yellow grey or light red grey. But, the colour of vegetation often does not show up as a natural green. This makes colour composites look unnatural and not visually pleasing.
SUMMARY OF THE INVENTION
Vegetation curves have a peak in the green range compared to the blue and red ranges. The spectral curves of soil reflectance rise proportional to the wavelength. However, the curve of clear water usually has a peak in blue range and then descends proportional to the wavelength. Therefore, when the blue, green and red bands of a multispectral sensor are displayed with blue, green and red colour, a near natural colour composite can be generated with water shown in blue, vegetation shown in green and soil shown in light yellow grey or light red grey. But, the colour of vegetation often does not show up as a natural green. This makes colour composites look unnatural and not visually pleasing.
SUMMARY OF THE INVENTION
[0005] The invention relates to a method for generating a natural colour image comprising the steps of generating a greenness band from a multispectral image including blue, green, red and near infrared bands and adjusting the green band using the greenness band.
[0006] In another embodiment, the invention relates to a method for generating a pan-sharpened natural colour image comprising the steps of generating a greenness band from pan-sharpened image bands including blue, green, red and near infrared bands and adjusting the pan-sharpened green band using the greenness band.
[0007] In another embodiment, the invention relates to a method for generating a pan-sharpened natural colour image comprising the steps of generating a greenness band from a panchromatic image and a pan-sharpened red band; and adjusting the pan-sharpened green band using the greenness band.
BRIEF DESCRIPTION OF THE DRAWINGS
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] Figure 1 is a graph showing general spectral reflectance curves of soil, water and vegetation with general spectral ranges of individual multispectral bands; and [0009] Figure 2 is a diagram showing spectral ranges of the multispectral bands and panchromatic band from individual satellites.
[0010] A simple and effective method is disclosed in the present invention to adjust the near natural colour of a satellite colour composite to a visually more pleasing natural colour. This method includes two steps: (1) extracting vegetation "greenness"
from available multispectral bands, and (2) adding (injecting) the "greenness" into the vegetation areas of the green band being displayed. In this way the vegetation areas can be made to look greener and fresher, so that the whole image appears more natural.
This method can be used to adjust the near natural colour of original multispectral composites and that of pan-sharpened composites.
Adjusting the colour of original near natural colour composites [0011] For a near natural colour composite with original multispectral bands, the vegetation "greenness" can be extracted using the equation:
GN = (NIRoYtg - Ro~g - ~.) j s (1) where GN is a greenness band, NIRor~~ is an original near infrared band, Ror~g is an original red band, ~, is a threshold and s is a scale factor.
from available multispectral bands, and (2) adding (injecting) the "greenness" into the vegetation areas of the green band being displayed. In this way the vegetation areas can be made to look greener and fresher, so that the whole image appears more natural.
This method can be used to adjust the near natural colour of original multispectral composites and that of pan-sharpened composites.
Adjusting the colour of original near natural colour composites [0011] For a near natural colour composite with original multispectral bands, the vegetation "greenness" can be extracted using the equation:
GN = (NIRoYtg - Ro~g - ~.) j s (1) where GN is a greenness band, NIRor~~ is an original near infrared band, Ror~g is an original red band, ~, is a threshold and s is a scale factor.
[0012] From Figure 1 it can be seen that the vegetation reflectance is very high in near infrared range and very low in red range. Consequently, vegetation covers have very high grey values in near infrared (NIR) band and low grey values in red (R) band. The subtraction of NIR band by R band (NIRorig - Rorig) results in a subtraction band with high grey values in vegetation areas (because of large grey value difference between the NIR and R bands), low grey values in soil areas, and negative grey values in water areas. To make sure that the colour adjustment just happens to vegetation areas, a threshold ~, needs to be introduced to segment non-vegetation areas in the subtraction band from vegetation areas, and then the non-vegetation areas need to be assigned with a grey value of zero. After this segmentation and assignment, only vegetation areas in the subtraction band contain grey values larger than zero, while other areas are all set to zero, resulting in a greenness band. The threshold can be identified manually and automatically. Some segmentation methods can be adopted for the segmentation, for example, the methods introduced by Parker J.R. (1997) [Algorithms for Image Processing and Computer Vision, John Wiley & Sons, New York, Chichester, 417 p.]. To control the magnitude of the greenness, a scale factor s can be introduced.
[0013] Alternative methods can be used to generate the greenness band. Instead of using the original red band (Ror;g), the original green or blue band can be used to replace the red band (RoY;g) in equation (1). This replacement also can results in a greenness band with high grey values in vegetation areas and zero grey value in other areas.
[0014] After the greenness band is generated, the greenness can be added (or injected) into the vegetation areas of the green band to adjust the green colour of the near natural colour composite:
Gndj ° Gorig ~' GN (2) where Ga~j is an adjusted green band, Gor;g is an original green band and GN
is a greenness band.
Gndj ° Gorig ~' GN (2) where Ga~j is an adjusted green band, Gor;g is an original green band and GN
is a greenness band.
(0015] For the improved natural colour image display, original blue band, adjusted green band, and original red band are displayed with blue, green and red colour, respectively.
Adjusting the colour of pan-sharpened near natural colour composites (0016] A similar method can be applied to improve the natural colour display of pan-sharpened colour composites. However, pan-sharpened near infrared and red bands need to be used to generate a high resolution greenness band:
GN~i = (NIRPS - R~s - ~,) / s (3) where GN~~ is a high resolution greenness band, NIR~s is a pan-sharpened near infrared band, R~s is a pan-sharpened red band, ~, is a threshold and s is a scale factor.
Adjusting the colour of pan-sharpened near natural colour composites (0016] A similar method can be applied to improve the natural colour display of pan-sharpened colour composites. However, pan-sharpened near infrared and red bands need to be used to generate a high resolution greenness band:
GN~i = (NIRPS - R~s - ~,) / s (3) where GN~~ is a high resolution greenness band, NIR~s is a pan-sharpened near infrared band, R~s is a pan-sharpened red band, ~, is a threshold and s is a scale factor.
[0017] An alternative for generating a high resolution greenness band is, instead of using pan-sharpened near infrared band, the high resolution panchromatic band can be used. This alternative also results in very good results. The method for extracting the high resolution greenness can be described as:
GNH = (Panor;g - R~s - ~.) j s (4) where GNH is a high resolution greenness band, Panorg is an original panchromatic band, Rps for pan-sharpened red band, ~, is a threshold and s is a scale factor.
GNH = (Panor;g - R~s - ~.) j s (4) where GNH is a high resolution greenness band, Panorg is an original panchromatic band, Rps for pan-sharpened red band, ~, is a threshold and s is a scale factor.
[0018] From Figure 2 it can be seen that the panchromatic bands of IKONOS, QuickBird and Landsat 7 cover a broad spectral range including near infrared. The average spectral reflectance of vegetation for this broad range is not as high as in near infrared range, but it is still significantly higher than the average reflectance of soil and water for the same range (see Figure 1). Therefore, vegetation is usually brighter than soil and water in such panchromatic images. The subtraction of Prtnorig band by R~s band (Panorag - R~s) results in high grey values in vegetation areas, very low grey values in soil areas and water areas. A threshold ~. is also needed to segment non-vegetation areas from vegetation areas to set the grey values of non-vegetation areas to zero. After this segmentation, only vegetation areas of the subtraction band contain grey values higher than zero, while other areas are zero, resulting in a high resolution greenness band (GNH). A scale factor s can be introduced to adjust the magnitude of the greenness.
[0019] Other variations for generating greenness bands or high-resolution greenness bands exist. For example, subtraction of near infrared band by green band or blue band and subtraction of green band by blue or red band can also generate greenness bands.
For high resolution greenness bands, pan-sharpened bands need to be involved.
The subtraction of original panchromatic band by pan-sharpened green or blue band can also result in a high resolution greenness band. However, the greenness bands generated with equations (1) (3) or (4) are more effective for improving the natural colour visualization of multispectral satellite images.
For high resolution greenness bands, pan-sharpened bands need to be involved.
The subtraction of original panchromatic band by pan-sharpened green or blue band can also result in a high resolution greenness band. However, the greenness bands generated with equations (1) (3) or (4) are more effective for improving the natural colour visualization of multispectral satellite images.
(0020] After the high resolution greenness band is generated, the greenness can be added (or injected) into the vegetation areas of the pan-sharpened green band to adjust the green colour of the pan-sharpened near natural colour composite:
GH,aa~ = GPs + GNH (5) where GHAa~ is an adjusted high resolution green band, GPs is a pan-sharpened green band and GNH is a high resolution greenness band.
GH,aa~ = GPs + GNH (5) where GHAa~ is an adjusted high resolution green band, GPs is a pan-sharpened green band and GNH is a high resolution greenness band.
[0021] For the display of the improved natural colour image, pan-sharpened blue band, adjusted high resolution green band, and pan-sharpened red band are displayed with blue, green and red colour, respectively.
[0022] In a preferred embodiment of the invention, the methods of the present invention are implemented by a programmed computer, and the method is used as a computer program product comprising a software tool stored on a machine-readable medium such as a CD Rom or floppy disc.
Claims (12)
1. A method for generating a natural colour image comprising the steps of generating a greenness band from a multispectral image including blue, green, red and near infrared bands and adjusting the green band using the greenness band.
2. A method according to claim 1 wherein the greenness band is generated mathematically using the equation:
GN = (NIR Orig - R Orig - .lambda.) / s where GN is a greenness band, NIR Orig is an original near infrared band, R
Orig is an original red band, .lambda. is a threshold and s is a scale factor.
GN = (NIR Orig - R Orig - .lambda.) / s where GN is a greenness band, NIR Orig is an original near infrared band, R
Orig is an original red band, .lambda. is a threshold and s is a scale factor.
3. A method according to claim 1, wherein the green band is adjusted mathematically using the equation:
G Adj = G Orig + GN
where G Adj is an adjusted green band, G Orig is an original green band and GN
is a greenness band.
G Adj = G Orig + GN
where G Adj is an adjusted green band, G Orig is an original green band and GN
is a greenness band.
4. A method for generating a pan-sharpened natural colour image comprising the steps of generating a greenness band from pan-sharpened image bands including blue, green, red and near infrared bands and adjusting the pan-sharpened green band using the greenness band.
5. A method according to claim 4, wherein the greenness band is mathematically generated using the equation:
GN H = (NIR PS - R PS - .lambda.) / s where GNH is a high resolution greenness band, NIR PS is a pan-sharpened near infrared band, R PS is a pan-sharpened red band, .lambda. is a threshold and s is a scale factor.
GN H = (NIR PS - R PS - .lambda.) / s where GNH is a high resolution greenness band, NIR PS is a pan-sharpened near infrared band, R PS is a pan-sharpened red band, .lambda. is a threshold and s is a scale factor.
6. A method for generating a pan-sharpened natural colour image comprising the steps of generating a greenness band from a panchromatic image and a pan-sharpened red band; and adjusting the pan-sharpened green band using the greenness band.
7. A method according to claim 6, wherein the greenness band is mathematically generated using the equation:
GN H = (Pan Orig - R PS - .lambda.) / s where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, R PS f or pan-sharpened red band, .lambda. is a threshold and s is a scale factor.
GN H = (Pan Orig - R PS - .lambda.) / s where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, R PS f or pan-sharpened red band, .lambda. is a threshold and s is a scale factor.
8. A method according to claim 4, wherein the pan-sharpened green band is adjusted mathematically using the equation:
G HAdj = G PS + GN H
G HAdj = G PS + GN H
9 where G HAdj is an adjusted pan-sharpened green band, G PS is an pan-sharpened green band and GN H is a high resolution greenness band.
9. A method according to claim 1, wherein the greenness band is generated using an equation selected from the group comprising :
GN = (NIR Orig - G Orig - .lambda.) / s and GN = (NIR Orig - B Orig - .lambda.) / s, where GN is a greenness band, NIR Orig is an original near infrared band, G
Orig is an original green band, B Orig is an original blue band, .lambda. is a threshold and s is a scale factor.
9. A method according to claim 1, wherein the greenness band is generated using an equation selected from the group comprising :
GN = (NIR Orig - G Orig - .lambda.) / s and GN = (NIR Orig - B Orig - .lambda.) / s, where GN is a greenness band, NIR Orig is an original near infrared band, G
Orig is an original green band, B Orig is an original blue band, .lambda. is a threshold and s is a scale factor.
10. A method according to claim 1, wherein the greenness band is generated using an equation selected from the group comprising:
GN H = (NIR PS - G PS - .lambda.) / s and GN H = (NIR PS - B PS - .lambda.) / s, where GN H is a high resolution greenness band, NIR PS is a pan-sharpened near infrared band, G PS is a pan-sharpened green band, B PS is a pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
GN H = (NIR PS - G PS - .lambda.) / s and GN H = (NIR PS - B PS - .lambda.) / s, where GN H is a high resolution greenness band, NIR PS is a pan-sharpened near infrared band, G PS is a pan-sharpened green band, B PS is a pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
11. A method according to claim 1 , wherein the greenness band is generated using an equation selected from the group comprising:
GN H = (Pan Orig - G PS - .lambda.) / s and GN H = (Pan Orig - B PS - .lambda.) / s, where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, G PS for pan-sharpened green band, B PS for pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
GN H = (Pan Orig - G PS - .lambda.) / s and GN H = (Pan Orig - B PS - .lambda.) / s, where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, G PS for pan-sharpened green band, B PS for pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
12. A method according to claim 7 , wherein the greenness bands are generated using an equation selected from the group comprising:
GN H = (Pan Orig - G PS - .lambda.) / s and GN H = (Pan Orig - B PS - .lambda.) / s, where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, G PS for pan-sharpened green band, B PS for pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
GN H = (Pan Orig - G PS - .lambda.) / s and GN H = (Pan Orig - B PS - .lambda.) / s, where GN H is a high resolution greenness band, Pan Orig is an original panchromatic band, G PS for pan-sharpened green band, B PS for pan-sharpened blue band, .lambda. is a threshold and s is a scale factor.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US10/756,781 US7379590B2 (en) | 2003-01-17 | 2004-01-14 | Method for generating natural colour satellite images |
US10/756,781 | 2004-01-14 |
Publications (1)
Publication Number | Publication Date |
---|---|
CA2491794A1 true CA2491794A1 (en) | 2005-07-14 |
Family
ID=34749375
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CA 2491794 Abandoned CA2491794A1 (en) | 2004-01-14 | 2005-01-10 | Method for generating natural colour satellite images |
Country Status (1)
Country | Link |
---|---|
CA (1) | CA2491794A1 (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113447136A (en) * | 2021-06-29 | 2021-09-28 | 北京华云星地通科技有限公司 | Multi-dimensional dynamic hybrid imaging method |
CN115082582A (en) * | 2022-06-09 | 2022-09-20 | 珠江水利委员会珠江水利科学研究院 | True color simulation method, system, equipment and medium for satellite remote sensing data |
-
2005
- 2005-01-10 CA CA 2491794 patent/CA2491794A1/en not_active Abandoned
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113447136A (en) * | 2021-06-29 | 2021-09-28 | 北京华云星地通科技有限公司 | Multi-dimensional dynamic hybrid imaging method |
CN115082582A (en) * | 2022-06-09 | 2022-09-20 | 珠江水利委员会珠江水利科学研究院 | True color simulation method, system, equipment and medium for satellite remote sensing data |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhang | Understanding image fusion | |
Tseng et al. | Automatic cloud removal from multi-temporal SPOT images | |
US8755597B1 (en) | Smart fusion of visible and infrared image data | |
US7853094B2 (en) | Color enhancement technique using skin color detection | |
Alparone et al. | Landsat ETM+ and SAR image fusion based on generalized intensity modulation | |
Zhang | A new automatic approach for effectively fusing Landsat 7 as well as IKONOS images | |
CN104182949B (en) | Image inking and fusing method and system based on histogram feature point registration | |
CN106709893B (en) | A kind of round-the-clock haze image sharpening restoration methods | |
Tu et al. | Best tradeoff for high-resolution image fusion to preserve spatial details and minimize color distortion | |
US20070262985A1 (en) | Image processing device, image processing method, program, storage medium and integrated circuit | |
US10455123B2 (en) | Method for increasing the saturation of an image, and corresponding device | |
Malpica | Hue adjustment to IHS pan-sharpened IKONOS imagery for vegetation enhancement | |
JP4421438B2 (en) | Image color balance correction system and method | |
US7379590B2 (en) | Method for generating natural colour satellite images | |
CN112446841B (en) | Self-adaptive image recovery method | |
Herrera-Arellano et al. | Visible-NIR image fusion based on top-hat transform | |
CN111489299B (en) | Defogging method for multispectral remote sensing satellite image | |
De Bethune et al. | Adaptive intensity matching filters: a new tool for multi-resolution data fusion | |
CN108537744A (en) | A kind of coloured image luminance component homomorphic filtering defogging method | |
CN115496685A (en) | Rapid cloud thinning method for high-resolution second-order satellite remote sensing image | |
CA2491794A1 (en) | Method for generating natural colour satellite images | |
Saroglu et al. | Fusion of multisensor remote sensing data: assessing the quality of resulting images | |
Herrera-Arellano et al. | Color outdoor image enhancement by V-NIR fusion and weighted luminance | |
JP2007183710A (en) | Color saturation correction system for green space | |
CN111539891A (en) | Wave band self-adaptive demisting optimization processing method for single remote sensing image |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
EEER | Examination request | ||
FZDE | Dead |
Effective date: 20121213 |