Firstly

this paper gives the property of wavelet transform of two dimensional noise

analyzes the relationship of wavelet transform modulus maxima to different decomposed class j and Lipschitz exponent

and points out how to determine and protect image edges.Then it explains the orthogonal wavelet transform of denoising based on soft and hard threshold

and puts forward a denoising method based on the wavelet modulus maxima and Neyman-Pearson principle. The method finds the optimal trade off between image denoising and protecting image edges.Based on the assumption that the observed image is the sum of the expected image and irregular corruptive noise

the qualitative and quantitative performance of our image denoising method is compared with others.Simulation results show the proposed method can efficiently denoise

such as increasing Signal-to-Noise Ratio(SNR)

lowing Mean Square Error(MSE) and Relative Entropy(RE)

while preserving the details of the original image.