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Roads and highways show up clearly in many bands of AVIRIS images. A typical lane in the U.S. is 12 feet wide, and the total width of a four lane highway, including 18 feet of paved shoulders, is 19.8 m. Such a highway will cover only a portion of any 20x20 m AVIRIS pixel that it traverses. The other portion of these pixels wil be usually covered by vegetation. An interesting problem is to precisely determine the location of a highway within the AVIRIS pixels that it traverses. This information may be used for alignment and spatial calibration of AVIRIS images. Also, since the reflection properties of highway surfaces do not change with time and they can be determined once and for all, such information can be of help in calculating and filtering out the atmospheric noise that contaminates AVIRIS measurements. The purpose of this report is to describe a method for sub-pixel localization of highways.
Roads and highways show up clearly in many bands of AVIRIS images. A typical lane in the U.S. is 12 feet wide, and the total width of a four lane highway, including 18 feet of paved shoulders, is 19.8 m. Such a highway will cover only a portion of any 20x20 m AVIRIS pixel that it traverses. The other portion of these pixels wil be usually covered by vegetation. An interesting problem is to precisely determine the location of a highway within the AVIRIS pixels that it traverses. This information may be used for alignment and spatial calibration of AVIRIS images. Also, since the reflection properties of highway surfaces do not change with time and they can be determined once and for all, such information can be of help in calculating and filtering out the atmospheric noise that contaminates AVIRIS measurements. The purpose of this report is to describe a method for sub-pixel localization of highways.
Sub-Pixel Localization of Highways in AVIRIS Images
Y. Salu (author)
1995
4 pages
Report
No indication
English
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