基于变分的MODIS 数据条带噪声去除方法

条带噪声是影响MODIS数据影像质量与反演精度的重要因素之一。针对MODIS数据中存在的三类条带噪声，提出了一种去除多类条带噪声的变分方法。该方法针对MODIS数据中条带噪声的类型设计相应的能量项：对于探测器间条带噪声和镜边条带噪声，采用直方图匹配变分项；对于随机噪声条带，采用单向消除项。各能量项通过权重系数组合构成总能量泛函，利用梯度下降流法最小化该泛函并离散数值化求解，从而实现条带噪声的消除。实验结果表明，提出的方法能够有效地去除MODIS数据的多类条带噪声。

Variational-based destriping method for MODIS data

Stripe noise is one of the crucial factors affecting the image quality and the inversion precision of moderate resolution imaging spectroradiometer（MODIS） data. Aiming at the characteristics of stripe noises in MODIS data, a novel variational based method for stripe noise reduction was proposed. An energy minimization problem was built by combining the two energy terms to find the solution as the destriped result. The first energy term uses variational histogram matching method to remove detector to detector stripes and mirror side stripes while the second energy term uses unidirectional remove method to reduce the random noisy stripes. The gradient descent flow was applied to minimize the total energy functional and the numerical scheme was presented. Experimental results show that the proposed method can reduce stripes in MODIS data effectively.