A Wavelet-Based Algorithm for Height from Gradients
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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