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With the improvements of spaceborne and airborne SAR system resolution, the applications of radar remote sensing has been extended to building 3D geometric information retrieval and reconstruction from urban SAR images, which is the foundation of build-up areas reconstruction and urban analysis. This paper mainly focuses on the problem of building height estimation from a single high resolution (HR) SAR image of urban scenes. A model based method combined with image segmentation framework of building height estimation is proposed. This method optimizes a new likelihood measure between the projection image from 3D geometric model of the buildings and the observed image over the heights hypothesis space. With assumption of the parallelepiped shapes, the SAR building area is partitioned into several regions. The new likelihood criterion then measures both the inner homogeneity of partitioned regions as well as their inter heterogeneity to achieve robust height hypothesis test. The optimization is done by simulated annealing in order to avoid local optimum. The experimental results performed on simulated SAR image data set valid the proposed method.