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An efficient coding algorithm for depth map images and videos, based on view synthesis distortion estimation, is proposed in this work. We first analyze how a depth error is related to a disparity error and how the disparity vector error affects the energy spectral density of a synthesized color video in the frequency domain. Based on the analysis, we propose an estimation technique to predict the view synthesis distortion without requiring the actual synthesis of intermediate view frames. To encode the depth information efficiently, we employ a Lagrangian cost function to minimize the view synthesis distortion subject to the constraint on a transmission bit rate. In addition, we develop a quantization scheme for residual depth data, which adaptively assigns bits according to block complexities. Simulation results demonstrate that the proposed depth video coding algorithm provides significantly better R-D performance than conventional algorithms.