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- W2499187871 abstract "A new Gaussian mixture model is used to improve the quality of propagation method for SFS in this paper. The improved algorithm can overcome most difficulties of propagation SFS method including slow convergence, interdependence of propagation nodes and error accumulation. To slow convergence and interdependence of propagation nodes, stable propagation source and integration path are used to make sure that the reconstruction work of each pixel in the image is independent. A Gaussian mixture model based on prior conditions is proposed to fix the error of integration. Good result has been achieved in the experiment for Lambert composite image of the front illumination." @default.
- W2499187871 created "2016-08-23" @default.
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- W2499187871 date "2016-01-01" @default.
- W2499187871 modified "2023-09-27" @default.
- W2499187871 title "Using Gaussian Mixture Model to Fix Errors in SFS Approach Based on Propagation" @default.
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- W2499187871 doi "https://doi.org/10.1007/978-981-10-2053-7_63" @default.
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