基于行列变换的恒模医学CT图像盲均衡算法

摘要

提出一种基于行列变换的降维恒模医学CT图像盲均衡算法.利用行列变换将图像信号转化为一维复值信号序列,构建了基于降维复值信号的医学CT图像盲均衡恒模代价函数,通过最陡下降法对代价函数进行迭代求解,从而获得图像的最优估计.仿真结果验证了算法的有效性,与传统算法相比,改善了峰值信噪比和恢复效果,迭代过程避免了矩阵逆运算,提高了运算效率.%A constant module blind equalization algorithm applied to medical CT image is proposed. The image is transformed into a plural value signal sequence by row-column transform. A constant modulus cost function based on dimension reduction is founded. The cost function is optimized by the steepest descent iteration, and the optimal image estimation is obtained. Simulation results show that the algorithm is effective. Comparing with the traditional algorithm, the peak signal to noise ratio and recovery effects are improved. Iterative process avoids matrix inversion to improve the efficiency of operations.