Aiming to address the issue of high complexity in estimating the parameters of the Attribute Scattering Center Model (ASCM) in Synthetic Aperture Radar (SAR) images, a sparse representation parameter estimation method that integrates information from the image domain is proposed. Firstly, the improved watershed algorithm is used to segment the scattering centers of different regions. Subsequently, based on the segmentation results, the frequency domain sparse representation dictionary is decoupled and applied in a serialized manner for scattering center parameter estimation using orthogonal matching pursuit to reduce algorithm complexity. Based on simulated data and measured MSTAR data, the effectiveness and efficiency of the proposed parameter extraction method were validated, and the optimization of theoretical complexity was analyzed. The results indicate that this method can significantly reduce the time and space complexity of the algorithm while achieving results close to those of the conventional orthogonal matching pursuit algorithm. The proposed method can be used for the efficient extraction of scattering center parameters in SAR images.