The acquisition of a three-dimensional (3-D) model in a real-world environment by scanning only sparsely can save us a great ammount range-sensing time. We address a new method for inferring missing range data based on the given intensity image and sparse range data. It is assumed that the known range data are given on a number of scan lines with 1 pixel width. This assumption is natural for a range sensor to acquire range data in a 3-D real-world environment. Both edge information of the intensity image and linear interpolation of the range data are used. Experiments show that this method gives very good results in inferring missing range data. It outperforms both the previous method and bilinear interpolation when a very small percentage of range data are known.