Stripe noise is common to most push-broom-type imagers and it perturbs both image quality analysis and the posterior processing. Based on the analysis of the the characteristics of the stripe noise, a new destriping method is proposed. By taking a quasi-homogeneous region as a reference, ideal data of the striped area can be estimated and be used to compute correction parameters. The cross-track edge information is extracted and processed using morphological techniques. Experiments carried out on real remote sensing data demonstrate that the proposed method can bring peak signal-to-noise ratio from 32 dB up to 48 dB. Compared to the existing typical algorithms, this destriping method can achieve lower image distortion, higher inverse coefficient of variation and peak signal-to-noise ratio. By reducing stripe noise and reserving useful details, the image quality is improved effectively.