On remote sensing imaging platform, quality of image is normally degraded by aliasing. The low-pass filter is commonly used to dealiasing. However low-pass filter introduces error for frequencies above its cutoff frequency. And the removed aliasing is also valuable information. To retain the valuable information, we propose a restoration based on band-pass filter. Firstly, the image is transformed into frequency domain. A restoration of reciprocal cell is adopted. It is based on geometrical characteristics of sensors. As a result, the superposition parts are separated from spectrum inside the bandwidth. Then aliasing spectrum is put into right position. Inverse filter is used to deblurring and remove the color noise. Finally, the shift invariance wavelet is combined to reduce the white noise. The test results indicate that the proposed restoration is better than conventional restorations. Valuable information of the restored spectrum is more than degraded spectrum. So this proposed method will be beneficial in the field of practical projects.