去除高光谱图像脉冲噪声的模型及算法

Modeland Algorithm for Removing Impulse Noise in Hyperspectral Images

在高光谱图像的获取和传输过程中,脉冲噪声对图像数据的影响比较大,尤其是当噪声浓度比较高时.为了有效地去除高光谱图像中的脉冲噪声,结合图像的特征和噪声特性,提出一种基于全变分的噪声去除算法.该算法考虑了高光谱图像的低秩特性和空间-光谱相关性,通过分裂bregman迭代的方法有效地去除了噪声,同时较好地保留图像的原有的结构信息.

In the process of acquisition and transmission of hyperspectral image,the influence of impulse noise in image data was relatively large,especially when the noise level was high.In order to effectively remove the impulse noise in hyperspectral image,a new method based on total variation is proposed to remove the impulse noise from the image.The algorithm considers the hyperspectral image of low rank characteristics and spatial spectral correlation,it effectively removes the noise through the split Bregman iteration method,and preserves the original structure informations of the image better.