基于约束共轭梯度的高能闪光照相图像复原算法
Constrained conjugate gradient algorithm for image restoration in high-energy radiography
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摘要: 针对闪光照相系统模糊较大、成像信噪比低的特点,提出了一种基于约束共轭梯度的闪光照相图像复原算法,将闪光照相图像复原问题转化为一个约束优化问题,引入基于非负、中值滤波和偏微分方程的光滑约束条件,并利用约束共轭梯度法迭代求最优解。数值试验表明,该算法能较好再现图像边缘信息,复原出的图像在信噪比和视觉方面都有较大提高。Abstract: A constrained conjugate gradient(CCG) restoration algorithm is proposed for badly blurred and noised high-energy radiography images. Constrained with prior knowledge, the algorithm converts the restoration problem to a constrained optimization one, which can be solved with the conjugate gradient algorithm. Since image restoration is an ill-posed problem, median filter and partial differential equation(PDE) are used to constrain the smoothness of deblurred image. Numerical experiment results show that the algorithm can properly retrieve edges and reduce noise simultaneously, and especially the signal to noise ratio(SNR) and subjective visual effect of the restored images are improved significantly.
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