To solve the problem of speckle noise in optical coherence tomography （OCT） system， an optical coherence tomography denoising algorithm based on bilateral random projection is proposed. Based on the high similarity of biological tissue structure between adjacent frames of 3D OCT image and the high resolution of image， the original OCT image signal is decomposed into noiseless low rank matrix， sparse matrix and noise matrix. The bilateral random projection algorithm is then used to solve the problem and extract the low rank matrix， so as to remove the noise and restore the noiseless image. The proposed algorithm is tested on the clinical data set， and the noise reduction effect is evaluated by signal to noise ratio （SNR）， contrast to noise ratio （CNR） and equivalent number of looks （ENL）. Experimental results show that compared with the robust principal component analysis algorithm， the proposed algorithm improves the SNR， CNR and ENL by 1.22 dB， 0.84 dB and 59.5， respectively. It can suppress speckle noise more effectively and has lower computational complexity.