Sparse-aperture imaging systems are desirable for aerospace applications because they can capture the same resolution as a filled aperture while reducing the systems’ size and weight. A novel sparse-aperture model named dual three-sub-aperture is proposed. By comparing with the famous Golay 6, dual three-sub-aperture is regarded as a better configuration for aerospace remote sensing. But the images of sparse-aperture systems become blurry because of the modulation transfer function (MTF) loss. It is necessary to optimize the image quality by image restoration process. In order to achieve ideal images, image filter technique has been studied. First, the imaging simulations of dual three-sub-aperture system and the Golay 6 with different fill factor are generated. The images formed by these systems are recovered by means of proper filters. Then different kinds of noises and different noise levels are added, various filters with different parameters are applied to recover these images. And the optimal deblurred images are gained. Through the quantitative evaluations of its image quality it is shown that the mentioned filter technique can be used to effectively improve the quality of the images degraded by the MTF’s loss, i.e. the details in images can be enhanced and its edges be sharpened.