基于改进逆滤波的衍射成像光谱仪图像复原方法

doi:10.11896／j.issn.1002-137X.2019.01.013

摘要/Abstract

摘要： 针对在衍射光谱仪(DOIS)成像中离焦谱段对准焦谱段成像造成干扰而导致的图像模糊问题,提出一种改进的逆滤波复原方法,旨在解决逆滤波中存在的不适定问题,并利用该方法对衍射光谱图像进行复原。改进的逆滤波算法通过引入正则化矩阵来改变原始问题的求解形式,将逆滤波函数进行正则化,从而减弱噪声对图像复原效果所产生的影响。通过将图像复原过程转换为矩阵求逆的过程,并在SVD算法求解过程中添加规则滤波器的方法,来调节正则化矩阵的形式以及参数的大小,达到了减弱矩阵的病态性并取得较优的复原效果的目的。实验结果表明,该方法能够有效地对衍射成像光谱仪图像进行复原,在一定程度上提高了拉普拉斯梯度以及图像质量指数(QI)值,同时减小了均方根(RMSE)值。所提方法能够抑制噪声干扰,增强图像清晰度,复原出与参考图相似度更高的单谱段图像,并能够获得更好的光谱曲线,有助于分析出地貌特征。

关键词: 逆滤波, 奇异值分解, 图像复原, 衍射成像光谱仪

Abstract: In order to solve the image-blurring problem caused by the interference from out-of-focus optical images in in-focus image within a diffractive optic imaging spectrometer (DOIS),an improved inverse filtering restoration method was proposed to solve the ill-posed problem in inverse filtering and restore the diffraction spectrum image.This method changes the solution of the primal problem by introducing a regularization matrix to regularize the inverse filtering function,thus suppressing the influences of noises on restored images.It achieves the purpose of reducing morbidity of the matrix and obtaining a better restoration result through the following three procedures:convert the image restoration process into a process of matrix inversion,add a regular filter to the SVD (singular value decomposition) method,and adjust the form of the regularization matrix and the values of parameters.Experiments show that the improved inverse filtering method is effective for restoring the spectral images formed with a diffractive optic imaging spectrometer.It can not only increase the Laplacian Gradient and QI(Quality Index) value,but also reduce RMSE(Root-Mean-Square Error) value to a certain extent.In the meantime,this method can suppress the noise interferences of the blurred images,enhance the image clarity,restore a single spectrum image with a higher similarity to the reference image,and obtain better spectral curves to analyze the geomorphological features.

Key words: Diffractive optic imaging spectrometer, Image restoration, Inverse filtering, Singular value decomposition

中图分类号:

TP391

张茗琪, 曹国, 陈强, 孙权森. 基于改进逆滤波的衍射成像光谱仪图像复原方法[J]. 计算机科学, 2019, 46(1): 86-93. https://doi.org/10.11896／j.issn.1002-137X.2019.01.013

ZHANG Ming-qi, CAO Guo, CHEN Qiang, SUN Quan-sen. Image Restoration Method Based on Improved Inverse Filtering for Diffractive Optic Imaging Spectrometer[J]. Computer Science, 2019, 46(1): 86-93. https://doi.org/10.11896／j.issn.1002-137X.2019.01.013

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