摘要
由条码扫描仪获得条码图像的过程可以用理想条码信号与扫描仪光学系统点扩散函数的卷积模型来描述。反卷积是消除由光学系统点扩散带来的模糊现象的最好办法。为克服反卷积的病态问题,研究了反卷积的正则化方法;针对条码信号的特点,构建了适合于条码信号复原的惩罚项,提出了条码信号的正则化复原算法及其适合于计算机运算的迭代算法。通过实验研究了算法在不同情况下的抗干扰能力。实验结果表明,正则化条码信号复原算法在消除系统点扩散函数的影响的同时能够很好地抑制噪声。
The process of the scanner obtaining bar code signal can be modeled as the convolution of the ideal bar code signal with the point spread function of scanner. Deconvolution is the best deblurring method. The regularization method of deconvolution is studied according to the characteristic of bar code signal in order to solve the ill-posed problem of deconvolution, the penalty item is constructed, and the computational regularization algorithm is proposed for the bar code signal recovery. The an ti jamming ability of the algorithm is tested in different instance by experiments. The experimental results show that the regularization algorithm of the restoration of bar code signal can restrain the noise effectively when it is eliminating the effect of the point spread function.
出处
《光学技术》
CAS
CSCD
北大核心
2006年第6期932-934,938,共4页
Optical Technique
关键词
条码图像
正则化
反卷积
迭代算法
误差品质
bar code image
regularization
deconvolution
iterative algorithm
error quality
