1. An image denoising method, comprising: acquiring image data of an image; performing wavelet decomposition on at least one component of three components of the image data to obtain a high frequency wavelet coefficient and a low frequency wavelet coefficient of each component, wherein the three components of the image data comprises a luminance component y and chrominance components u and v; performing recursive denoising on the low frequency wavelet coefficient of each component to obtain a denoised low frequency wavelet coefficient of each component; performing wavelet reconstruction according to the high frequency wavelet coefficient of each component and the denoised low frequency wavelet coefficient of each component to obtain at least one denoised component; combining the three denoised components to obtain denoised image data when at least one denoised component is three components; combining at least one denoised component with the other one or two components of the three components to obtain denoised image data when at least one denoised component is one or two components; and performing shrinkage function denoising on the high frequency wavelet coefficient of each component based on edge information, wherein performing shrinkage function denoising on the high frequency wavelet coefficient of each component based on the edge information comprises performing denoising on the high frequency wavelet coefficient of each component according to the following formula; 
 y=αx +(1−α) h ( x ), wherein α is a parameter related to an edge intensity wherein h(x) is a shrinkage function about x, and wherein performing wavelet reconstruction according to the high frequency wavelet coefficient of each component and the denoised low frequency wavelet coefficient of each component to obtain at least one denoised component comprises performing wavelet reconstruction according to the denoised high frequency wavelet coefficient of each component and the denoised low frequency wavelet coefficient of each component to obtain at least one denoised component.