An adaptive image denoising scheme using pixel classification and wavelet transform is propose.At first,an initial denoised image is obtained by one of conventional image denoising methods.Then the image is partitioned into image blocks with the same size,and the spatial frequency of each image block is calculated.The different thresholds are employed to the image blocks according to the normalized spatial frequencies.The small threshold is used to the image block with the high spatial frequency,or the large threshold is employed.Experimental results show that this approach can reduce the image noise effectively,while little image detail is lost.This algorithm is superior to the conventional wavelet image denoising approaches with 3.4 dB improvement of peak signal noise rate(PSNR) at most.