Destriping Imaging Spectrometer Data by an Improved Moment Matching Method
成像光谱仪图像条带噪声去除的改进矩匹配方法

Striping is an important factor that influences image quality acquired by linear array CCD blocks.This may be more crucial for spectrometers because of the imperfect calibration of the detector characteristics and the necessity of higher CCD quality,which results in the most common striping.This paper firstly discussed the main reason causing stripes.Then we compared some stripingremoval algorithms and their limitations.Based on this consideration,we pointout that the standard moment matching method changes the mean value distrbution of image in line or column arrangement. This is especiallythe case forsmall size images.We presentsome approaches to simulate and calibrate the image grayval- ue distribution.The purpose of these methods we embraced here is to recover the truth of the mean value distribution of ground radiance.As an emphasis,we mainly discussed the theories and processes of three kinds of mean value fitting ap- proaches:the mean value compensation method,Fourier transformation method and correlation method. After discussing the methods,we used an 890×770 size test image acquired by an imaging spectrometer to experi- ment our theories.Through combining moment matchingwith these post-processing techniques,we successfully reduced stripes and improved the image quality.Finally,we visually and quantitatively assessed the quality of the resulted images.