We present a 3D imaging method to reduce speckle noise that exists in coherent imaging systems. This approach is based on integral imaging (II). The elemental images set having speckle-noise patterns of a 3D object is obtained by II technique under coherent illumination. The computational geometrical ray-propagation algorithm is applied to the elemental images in order to reconstruct the original 3D object. A uniform probability-density function is assumed for modeling the phase distribution of the speckle patterns. The statistical point estimator is used for 3D speckle removal. Speckle index is calculated to compare the computational reconstruction using the proposed method with that of conventional coherent image degraded by speckle patterns for 3D object reconstruction and by object recognition. Experimental results are presented. The speckle index, mean square error, and signal-to-noise ratio are used as performance metrics and are shown to have been significantly improved by the proposed method to reduce speckle noise in the 3D object reconstruction. 3D reconstruction experiments of objects with reduced speckle noise are presented. To the best of our knowledge, this is the first report on 3D speckle removal using II and statistical estimation algorithms.