基于矩匹配和变分方法的MODIS条带去除模型

针对MODIS影像条带噪声的特点，提出了一种结合矩匹配和变分方法的条带去除模型。首先采用矩匹配方法去除多行和宽行条带噪声，然后基于改进的条带检测方法定位矩匹配后的残余条带，最后基于变分条带去除模型，使用Split Bregman迭代求解以去除条带。实验结果表明，该方法能够有效地去除MODIS影像中的条带噪声，并能有效地保持图像中的细节信息。与直方图匹配、矩匹配、低通滤波及单向变分去条带算法相比，本文模型取得了更为理想的去噪效果。

Destriping Model of MODIS Image Based on Moment Matching and Variational Approach

A novel model for stripe noise reduction was proposed by combining moment matching with variational method, based on analyzing the characteristics of stripe noises in moderate resolution imaging spectroradiometer (MODIS) data. Firstly, multi-line and wide-line stripes were denoised by the moment matching method. Secondly, the stripes left in the result image were located by the improved stripe detection algorithm. Finally, based on the variational destrping model, Split Bregman iteration was adopted to reduce the strip noises. Experimental results show that the proposed algorithm can remove stripes in MODIS data and preserve the details of the image effectively. Compared with the destriping models including histogram matching, moment matching, low-pass filter and unidirectional variational destriping, the proposed method obtained more ideal results.