Creation of 3D images through remote sensing is a topic of interest in many applications such as terrain / building modeling and automatic target recognition (ATR). Several photogrammetry-based methods have been proposed that derive 3D information from digital images from different perspectives, and lidar- based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registra­ tion alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and lack of proper convergence in the merging process. This paper presents a method to create 3D images that uses the unique properties of texel images (pixel­ fused lidar and digital imagery) to improve the quality and robustness of fused 3D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3D points are fused at the sensor level, more accurate 3D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods.