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- W4387677968 abstract "This study presents a sparse window-based stereo-matching algorithm that enhances the accuracy and efficiency of the semi-global matching algorithm. Unlike traditional methods, this algorithm processes pixel areas based on their texture features, resulting in more efficient encoding. The proposed approach systematically samples pixels within the original encoding window to reduce the number of pixels involved in the process. Additionally, using the FAST feature detection method distinguishes texture areas and applies different encoding processes for each area to obtain the feature encoding of the center pixels. Experimental results show that compared with traditional semi-global stereo matching algorithms, our proposed sparse window-based algorithm improves processing speed by 0.06 seconds and reduces average error by 10.92%." @default.
- W4387677968 created "2023-10-17" @default.
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- W4387677968 date "2023-08-30" @default.
- W4387677968 modified "2023-10-17" @default.
- W4387677968 title "Improved Stereo Matching Algorithm Based on Sparse Window" @default.
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- W4387677968 doi "https://doi.org/10.1109/icac57885.2023.10275311" @default.
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