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In this paper, an approach to the automatic reconstruction of 3D simple building objects from multi-aspect metric-resolution SAR images is proposed. The edge detector of constant false alarm rate (CFAR) and a parallel Hough transform technique are first employed to extract the parallelogram-like image of the building walls in SAR image. A set of probability density functions is presented to describe the extracted random wall-images and their multi-aspect coherence. Then the maximum-likelihood estimation of object is derived from its multi-aspect object-images. A hybrid priority criterion is defined to evaluate the reliability of reconstruction result, based on which, an automatic reconstruction algorithm is further devised to match object-images of different aspects and finally reconstruct the building objects. Four-aspect Pi-SAR images over Sendai, Japan are adopted for reconstruction. The results show the fidelity of the whole process chain and the feasibility of 3D objects automatic reconstruction from multi-aspect SAR images.