A computer implemented method for image processing comprising: performing (101, 201, 301,401) edge identification on an image; determining (102, 202, 302, 402) a filtering kernel for a filtering processing on the image according to a result of the edge identification; performing (103, 203, 303, 403) the filtering processing on the image based on the filtering kernel to obtain a low-frequency image and a high-frequency image corresponding to the image; and performing an enhancement processing for the high-frequency image using a first gain coefficient of the high-frequency image to obtain an enhanced high-frequency image and performing image fusion for the low-frequency image and the enhanced high-frequency image to obtain a processed image; wherein a low-pass filtering processing is performed on the image based on the filtering kernel to obtain the low-frequency and the low-frequency image is subtracted from the original image to obtain the high-frequency image; characterized by: the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: determining an edge coefficient in the image according to the result of the edge identification, wherein the edge coefficient indicates edge information in the image, wherein the larger the edge coefficient is the more edge information the image comprises, whereas the smaller the edge coefficient is, the less edge information the image comprises; and determining a size of the filtering kernel according to the edge coefficient, wherein the size of the filtering kernel is positively correlated with the edge coefficient; or the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: dividing the image into a non-background region where edge information is located and a background region; and adaptively determining a size of the filtering kernel according to a location where edge information is located, wherein the size of the filtering kernel for the non-background region is larger than that for the background region. performing (101, 201, 301,401) edge identification on an image; determining (102, 202, 302, 402) a filtering kernel for a filtering processing on the image according to a result of the edge identification; performing (103, 203, 303, 403) the filtering processing on the image based on the filtering kernel to obtain a low-frequency image and a high-frequency image corresponding to the image; and performing an enhancement processing for the high-frequency image using a first gain coefficient of the high-frequency image to obtain an enhanced high-frequency image and performing image fusion for the low-frequency image and the enhanced high-frequency image to obtain a processed image; wherein a low-pass filtering processing is performed on the image based on the filtering kernel to obtain the low-frequency and the low-frequency image is subtracted from the original image to obtain the high-frequency image; characterized by: the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: determining an edge coefficient in the image according to the result of the edge identification, wherein the edge coefficient indicates edge information in the image, wherein the larger the edge coefficient is the more edge information the image comprises, whereas the smaller the edge coefficient is, the less edge information the image comprises; and determining a size of the filtering kernel according to the edge coefficient, wherein the size of the filtering kernel is positively correlated with the edge coefficient; or the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: dividing the image into a non-background region where edge information is located and a background region; and adaptively determining a size of the filtering kernel according to a location where edge information is located, wherein the size of the filtering kernel for the non-background region is larger than that for the background region. the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: determining an edge coefficient in the image according to the result of the edge identification, wherein the edge coefficient indicates edge information in the image, wherein the larger the edge coefficient is the more edge information the image comprises, whereas the smaller the edge coefficient is, the less edge information the image comprises; and determining a size of the filtering kernel according to the edge coefficient, wherein the size of the filtering kernel is positively correlated with the edge coefficient; or the determining (102, 202, 302, 402) the filtering kernel for a filtering processing on the image according to the result of the edge identification comprises: dividing the image into a non-background region where edge information is located and a background region; and adaptively determining a size of the filtering kernel according to a location where edge information is located, wherein the size of the filtering kernel for the non-background region is larger than that for the background region.