To address the problems of large similar block matching errors and insufficient protection of image details in the classical BM3D denoising algorithm, an improved BM3D image denoising algorithm based on rotated blocks is proposed. The new algorithm firstly rotates the reference block at different angles to obtain the rotating block, and then performs the similar block matching process through the rotating block; then uses low-rank regularization to replace the hard threshold filtering in the traditional algorithm; finally, the BM3D algorithm combining rotated block matching and low-rank regularization is adaptively adjusted to improve the denoising effect in uniform image regions. Experimental results show that the new algorithm has a higher matching degree of similar blocks, and the peak signal to noise ratio (PSNR) is improved by 0.5dB on average compared with the classical algorithm, effectively preserving image edges and texture details.