THE EFFECT OF SHADOW AREA ON SGM ALGORITHM AND DISPARITY MAP REFINEMENT FROM HIGH RESOLUTION SATELLITE STEREO IMAGES
Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban areas and images with shadow areas. As i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W4/281/2017/isprs-archives-XLII-4-W4-281-2017.pdf |
| Summary: | Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry
community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban
areas and images with shadow areas. As it can be seen, unfortunately the SGM algorithm computes highly noisy disparity values for
shadow areas around the tall neighborhood buildings due to mismatching in these lower entropy areas. In this paper, a new method is
developed to refine the disparity map in shadow areas. The method is based on the integration of potential of panchromatic and
multispectral image data to detect shadow areas in object level. In addition, a RANSAC plane fitting and morphological filtering are
employed to refine the disparity map. The results on a stereo pair of GeoEye-1 captured over Qom city in Iran, shows a significant
increase in the rate of matched pixels compared to standard SGM algorithm. |
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| ISSN: | 1682-1750 2194-9034 |