Abstract: To solve the problem of the loss of information in texture areas using traditional image denoising algorithms, we propose an algorithm for image denoising and enhancing based on 3DDCT according to the characteristic that the number of non-zero discrete Cosine transform (DCT) coefficients in smooth regions is fewer. First, similar blocks of the images is put to a block group according to l2 normal form; second, 2DDCT transformation is applied to each block and the threshold for the first denoising is used according to the correlation of pixels within the block; after that, 1DDCT transformation is applied on block groups according to the similarity between the corresponding pixels; then the threshold is used for a second time denoising; third, α power expansion is made to the non-zero coefficients in high frequency regions of 3D transform domain; finally, the proceed image is combined with Kaiser Window function. Compared with traditional algorithms, the new algorithm has a better visual performance because of its abilities to enlarge non-zero DCT coefficients in high frequency areas and to enhance information in texture and edge areas at the same time.