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A new technique to remove false topographic perception phenomenon and its impacts in image interpretation
- Source :
- International Journal of Remote Sensing. 28:811-821
- Publication Year :
- 2007
- Publisher :
- Informa UK Limited, 2007.
-
Abstract
- All Sun-synchronous remote sensing satellites, during day passes always acquire images when the illumination source (i.e. Sun position) is from the SE direction. The typical solar-illumination-source-observer position creates a false topographic perception phenomenon (FTPP) in the images of any rugged terrain (e.g. Himalayas, Alps etc.). Due to the presence of FTPP, valleys appear as ridges and vice versa, especially in rugged terrain. The correction of FTPP is necessary because it creates confusion in the minds of interpreters due to inherent inverse topographic perception. This paper explains the development of a new approach to remove FTPP. It has been successfully demonstrated using an IRS-1D-LISS-III image of part of the Himalayas, which represents highly rugged terrain. In this newly developed image-processing technique; a red-green-blue (RGB) image is first transformed into intensity-hue-saturation (IHS) channels, then the original intensity channel is inverted and later retransformed back from an IHS to a RGB image. After this retransformation, the RGB image is then colour balanced with original false colour composite. The final image product is free from FTPP and also contains almost the same image information. This method is an easy and quicker method to remove FTPP in comparison to the already available methods (e.g. image rotation by 180°; creating an image negative; using an opposite illuminated shaded relief model as an intensity image during IHS to RGB retransformation) for FTPP correction. Further, this paper discusses the relative advantages of this new method in comparison to previous methods in light of image classification and lineament interpretation carried out using images with and without FTPP.
- Subjects :
- Contextual image classification
Computer science
business.industry
media_common.quotation_subject
Terrain
Interpretation (model theory)
Image (mathematics)
Position (vector)
Perception
General Earth and Planetary Sciences
RGB color model
Computer vision
Artificial intelligence
business
Rotation (mathematics)
Remote sensing
media_common
Subjects
Details
- ISSN :
- 13665901 and 01431161
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- International Journal of Remote Sensing
- Accession number :
- edsair.doi...........ca780ff7e339f629c7aedd6e40d69bee
- Full Text :
- https://doi.org/10.1080/01431160701269796