庞大的采样次数和较低的信噪比(SNR)一直制约着鬼成像的实际应用进程，传统的鬼成像利用高斯型随机光场进行成像，而高斯矩阵的非正交性引入了散斑相关性噪声，降低了信噪比和成像效率。为此提出了利用局部的Hadamard 矩阵对目标进行测量，并以低分辨率的清晰成像作为高分辨率成像的先验知识实现去噪，可以有效避免相关性噪声。通过仿真以及实验表明，与传统的重构方法相比，本文方法可以提高信噪比和成像效率。

Large number of sampling and low signal-to-noise ratio (SNR) limit the practical application of ghost imaging process. The traditional ghost imaging using Gaussian random field imaging ，however, speckle noise is introduced by the non-orthogonality of Gaussian matrix , which decreases the SNR and efficiency. Therefore, local Hadamard matrix is used to measure the target, and the clear image of low-resolution image is utilized as a prior knowledge for high resolution image to achieve denoising, which can effectively eliminate the correlated noise. Simulation and experimental results show that, comparing with the traditional reconstruction methods, the proposed method can increase the SNR and imaging efficiency.