In order to alleviate the pressure of subsequent data acquisition and processing systems caused by high data volume in Frequency Domain Optical Coherence Tomography (FD-OCT), and to address the contradiction between imaging time and imaging quality, we introduced compressed sensing technology and focus on the reconstruction algorithm in this technology. First, we analyzed the framework of the compressed sensing technology, the frequency domain OCT image was sparsely represented by Discrete Cosine Transform. Next, we used Gaussian random matrices to perform linear observations on OCT images. Then, we studied the principle of FOCUSS (Focal Underdetermined System Solver) reconstruction algorithm, and combined the block idea, introduced the regular term lp norm and embed anisotropic smoothing operator in the algorithm. Finally, we combined all the small image blocks to obtain the compressed sensing reconstruction result of the whole frequency domain OCT image. Experimental results indicate that the running time of the improved reconstruction algorithm is shortened from 78.65 s to 1.89 s, and the image block effect is significantly improved, the PSNR value of the reconstructed image is improved by 1.6-2.7 dB, and the SSIM value can reach 0.938 3. Compressed sensing technology can accurately reconstruct the original frequency domain OCT image with a small amount of sampled data. The improved FOCUSS reconstruction algorithm can achieve the balance of frequency domain OCT image reconstruction efficiency and reconstruction quality to some extent.