基于噪声建模的遥感卫星图像分层去噪算法

Remote Sensing Satellite Image De-noising Based on Noise-modeling

在遥感卫星成像机理分析的基础上,提出一种分层去噪算法,该算法引入了噪声分类建模的思想,根据噪声模型的特殊性分层降噪,最后进行轮廓填充恢复.实验结果表明,该算法不仅能有效抑制多类噪声,也能很好地保持图像的边缘细节信息,在经典去噪评价指标信噪比SNR、均方误差MSE上也都达到了很好的实验标准,具有良好的去噪性能.

This paper promotes a new method to de-noise at different stages.Basing at the principle of remote sensing devices to capture images,it introduces an idea of noise-modeling,then de-noises images by the characteristics of different noise models,and finally,recovers the edge and details of the images.Experiments prove that,it can not only de-noise multiple noises efficiently,but also keep the edge and detail information well.It also tests well in classical targets such as SNR and MSE.In a word,this method functions well in de-noising.