一种改进的矩匹配高光谱图像非均匀校正算法

An Improved Moment Matching Algorithm for Non-Uniform Correction of Hyperspectral Images

为进一步抑制遥感图像的非均匀噪声,首先分析了空间遥感高光谱图像条带噪声产生的原因及噪声模型,进而提出一种基于窗口阈值判决的改进矩匹配算法。选取相对平坦,且条带噪声与背景对比较明显的区域进行阈值估算,并选取参考均值、标准差和条带阈值判决对条带噪声进行矩匹配处理。实验结果表明,所提算法的峰值信噪比相对传统方法至少提高了6.2163dB,均方误差最小降低了5.9630,结构相似度至少提高了0.254。与传统方法相比,采用所提方法处理后的图像变异逆系数有所提高,图像横向梯度与标准差有所降低,该方法还去除了图像中的条带噪声,保留了原始图像的细节信息。

In order to further restrain the non-uniform noise of remote sensing images,we analyze the the causes and noise models of stripe noise in the spatial remote sensing hyperspectral image,and then propose a moment matching algorithm based on the window threshold decision.The window threshold can be estimated based on the flat region and the obviously striped region.Further,moment matching can be achieved with respect to the images containing stripe noise based on the referent mean,standard deviation,and stripe threshold determination.The experimental results denote that compared with the traditional methods,the peak signal-to-noise ratio increases by at least6.2163 dB,the mean-square error decreases by at least 5.9630,and the structural similarity increases by at least0.254.When compared with the traditional methods,an improved image variation inverse coefficient can be obtained using the proposed method;further,the lateral gradient and standard deviation of the image decrease,the image stripe noise is effectively removed,and the original image details are preserved.