A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
1.1. Background and Related Works
1.2. The Proposed Approach
2.1. Water Block Extraction
- Seed point detection is conducted on the whole image with a fixed sampling interval (set as 5), and then all detected seed points are recorded.
- Seed point growth for all unprocessed seed points in turn to extract water blocks. If one seed point has been processed or belongs to a water block already detected, it will be marked as processed immediately.
2.2. Disparity Range Calculation
2.3. Block Matching
- Considering that the water block should be a plane, it is reasonable to assume that all pixels belonging to the same block share the same disparity with high probability. Thus, it is natural to use the automatically detected blocks as the matching primitives in our method.
- The image pair in this study has been already geometrically rectified, so it is allowed that the search space is limited to the one-dimension direction based on the epipolar constraint.
- In this study block matching strategy is embedded into dense matching processing. Thus, a reasonable disparity range, which is crucial to low complexity and high accuracy, can be derived from the dense matching result.
- Considering the two images of the image pair in this study are obtained by the same satellite simultaneously, it can be accepted that there is no complex but only linear radiation difference between them, which is very useful for reliable matching cost design.
2.3.1. Matching Cost Calculation and Disparity Estimation
2.3.2. Geometrical Deformation Process
2.3.3. Mismatch Elimination and Interpolation
2.4. Dense Matching
2.5. DSM Generation
3.1. The Experimental Platform and Data
3.2. Experiment on Seed Point Extraction and ROI Extraction
3.3. Experiment on ROI Matching
3.4. DSM Quality Assessment
4.1. Advancements of The Proposed Method
4.2. Limitations of the Proposed Method
Conflicts of Interest
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|Satellite Image Pairs|
|Image size(pixel)||16281 16364|
|ROI||Pixels||Area (km2)||Height (m)|
|Method||Indicator||Image Pair Block1|
|Image Pair Block2|
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Yang, W.; Li, X.; Yang, B.; Fu, Y. A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas. Remote Sens. 2020, 12, 870. https://doi.org/10.3390/rs12050870
Yang W, Li X, Yang B, Fu Y. A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas. Remote Sensing. 2020; 12(5):870. https://doi.org/10.3390/rs12050870Chicago/Turabian Style
Yang, Wenhuan, Xin Li, Bo Yang, and Yu Fu. 2020. "A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas" Remote Sensing 12, no. 5: 870. https://doi.org/10.3390/rs12050870