稀疏表示的夏克-哈特曼波前传感器信号提取

The Extraction of Signal in Shack-Hartmann Wavefront Sensor Based on Sparse Representation

由于背景噪声及探测器噪声的存在,夏克-哈特曼波前传感器质心探测误差较大,本文提出了一种在稀疏域去除背景噪声及探测器噪声的方法。首先采用二维高斯模型生成光斑信号样本图像,构造超完备目标字典,依次对测试图像分块计算其在超完备字典中的表示系数,利用噪声、背景和目标表示系数的不同,通过认为设定阈值来判别该图像块是否为光斑信号。结果表明,本文处理方法能够较好的提取出光斑信号,且与减阈值算法相比,其处理后质心偏差、RMS及PV值都较小。

Due to the background noise and the detector noise,the centroid error of Shack-Hartmann wavefront sensor is relatively large.A method to filter the noise in sparse region is proposed.First,the sample image is generated by using the two-dimension Gauss model and the over-complete target dictionary is constructed.Then,the sub-image blocks of the test image are extracted successively and the corresponding coefficients are calculated with the constructed over-complete target dictionary.Since the coefficients between the noise and the target are large different,the difference by setting a threshold is used to subtract the target.Experimental results show that,the target can be well subtracted,while the centroid deviation and the RMS and PV of the centroid are smaller than using the method of subtracting threshold.