Three dimensional (3D) object reconstruction from a series of cross sectional images has found many applications, such as computer vision, medical imaging. In this paper, we proposed a wavelet based interpolation for 3D reconstruction. In this scheme, a contour signal of interested object is decomposed by using multiresolution wavelet bases. The length of a 'filled' contours is first estimated from the two lengths of a coarsest scales of the two adjacent slices, refined by the lengths of the finer scales. The interslice contour estimation is obtained by the inverse wavelet transform. A series of CT liver images is used to test the performance of our method. Experiments show that our method can obtain satisfactory reconstruction surface. The advantages of our method are (i) no need of feature matching, which is a time consuming process and usually result in false matching results and (ii) fast algorithms for wavelet transforms can be implemented. Thus, our method is not only reliable for practical images but also computationally efficient.