An image processing method, comprising: accessing , luminance components of respective pixel points in an image, and generating a luminance distribution of the image according to the luminance components ; generating , a luminance mapping relation based on a standard luminance distribution corresponding to a scene of the image and the luminance distribution of the image; and adjusting , the luminance components of the respective pixel points of the image according to the luminance mapping relation to generate a first processed image; the image processing method characterized by further comprising: performing , edge recognition of the first processed image; determining , a filtering kernel that performs a filtering processing of the image according to an edge recognition result; performing , a filtering processing of the first processed image based on the filtering kernel to obtain a low-frequency image corresponding to the first processed image and a high-frequency image corresponding to the first processed image; and determining , a first gain coefficient of the high-frequency image, performing an enhancement processing of the high-frequency image according to the first gain coefficient, and performing an image fusion of the low-frequency image and an enhanced high-frequency image to obtain a second processed image. accessing , luminance components of respective pixel points in an image, and generating a luminance distribution of the image according to the luminance components ; generating , a luminance mapping relation based on a standard luminance distribution corresponding to a scene of the image and the luminance distribution of the image; and adjusting , the luminance components of the respective pixel points of the image according to the luminance mapping relation to generate a first processed image; the image processing method characterized by further comprising: performing , edge recognition of the first processed image; determining , a filtering kernel that performs a filtering processing of the image according to an edge recognition result; performing , a filtering processing of the first processed image based on the filtering kernel to obtain a low-frequency image corresponding to the first processed image and a high-frequency image corresponding to the first processed image; and determining , a first gain coefficient of the high-frequency image, performing an enhancement processing of the high-frequency image according to the first gain coefficient, and performing an image fusion of the low-frequency image and an enhanced high-frequency image to obtain a second processed image. performing , edge recognition of the first processed image; determining , a filtering kernel that performs a filtering processing of the image according to an edge recognition result; performing , a filtering processing of the first processed image based on the filtering kernel to obtain a low-frequency image corresponding to the first processed image and a high-frequency image corresponding to the first processed image; and determining , a first gain coefficient of the high-frequency image, performing an enhancement processing of the high-frequency image according to the first gain coefficient, and performing an image fusion of the low-frequency image and an enhanced high-frequency image to obtain a second processed image. <EOS>