基于全变分正则化的高能闪光照相消模糊图像重建算法
Total variation-based regularization algorithm for image deblur-reconstruction in high energy X-ray radiography
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摘要: 针对高能闪光照相投影图像消模糊难度大的问题，提出了一种基于全变分正则化的消模糊图像重建算法，该算法根据闪光照相的成像特点，将客体的纵向截面作为一个整体来进行建模，并在重建方程中考虑了模糊因素，然后采用全变分范数作为正则项，构建了用于消模糊图像重建的展平泛函，将消模糊图像重建问题转化为能量泛函极小化问题，通过固定点迭代算法求解图像重建问题的最小化解。数值模拟结果表明：该算法由于考虑了闪光照相成像时的图像模糊因素，在重建时能够较好地消除模糊对重建结果的影响，在抑制噪声的同时能较好地保持图像的边缘信息，有利于提高重建图像的质量。Abstract: According to the problem of deblur of flash radiographic image with low signal-to-noise ratio, a total variation (TV) regularization based image deblur-reconstruction algorithm is proposed. Considerring the blurring of the image system, the deblur-reconstruction model in new algorithm is established for three-dimensional (3D) object based on flash radiographic characteristics. Then a TV-norm is used as regularized term to construct a smoothing function for image deblur-reconstruction. Thus, the problem of image deblur-reconstruction is transformed in to a problem of a functional minimization. The fixed point iteration (FPI) scheme is introduced to solve the problem. The numerical experimental results show that to some extent, the new algorithm can eliminate the influence on reconstruction
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Key words:
- flash radiography /
- total variation /
- regularization /
- deblur /
- image reconstruction
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