Abstract
This paper presents a wavelet-based algorithm for height from gradients. The tensor product of the third-order Daubechies’ scaling functions is used to span the solution space. The surface height is described as a linear combination of a set of the scaling basis functions. This method efficiently discretizes the cost function associated with the height from gradients problem. After discretization, the height from gradients problem becomes a discrete minimization problem rather than discretized PDE’s. To solve the minimization problem, perturbation method is used. The surface height is finally decided after finding the weight coeffcients.
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© 2001 Springer-Verlag Berlin Heidelberg
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Wei, T., Klette, R. (2001). A Wavelet-Based Algorithm for Height from Gradients. In: Klette, R., Peleg, S., Sommer, G. (eds) Robot Vision. RobVis 2001. Lecture Notes in Computer Science, vol 1998. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44690-7_11
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DOI: https://doi.org/10.1007/3-540-44690-7_11
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