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 discretize 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 coefficients. 1 The University of Auckland, Tamaki Campus, Centre for Image Technology and Robotics, Computer Vision Unit, Auckland, New Zealand