3D scene modelling by sinusoid encoded illumination

A depth estimation algorithm is proposed in this paper. In the algorithm, the sinusoidally-encoded image is used to estimate the depth by decoding the signal's propagating phase. It is based on the assumption that a planar surface should have a constant first derivative on the propagating phase. Since the major operation is differentiating, this method is highly sensitive to the noise disturbance of measurements. Random noise can be induced by the imaging channel, by unstable lighting, or by the roughness of the working environment. To subdue the influence of induced the noise a reinforced k-gradient operation is alternatively used. The algorithm is then applied to the synthetic images containing various amounts of noise to test its performance. Experimental results indicate that the estimated depth error is kept within 2% when k is greater than or equal to 6 - even when a Gaussian noise with standard deviation up to 1.5 is applied.