推扫式遥感相机图像条带噪声去除方法

Destriping of Remote Sensing Images with Applications to Push-Broom-Type Cameras

推扫式遥感相机图像中存在微弱的条带噪声,干扰数据分析精度和后续图像处理。在分析其噪声特性后,提出了一种去除条带噪声的方法。以相对平坦区作为参考图像,获取垂轨边缘信息并进行图像形态学处理,从而获得各像元的校正参数来对图像进行补偿。实验表明,可以将遥感图像峰值信噪比由32dB提升到48dB;相较于目前已有的去条带噪声方法,该方法处理的图像畸变较小,变异逆系数及信噪比提升幅度较大,在有效去除条带噪声的同时保留了原图像灰度信息,提高了图像质量。

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.