1. A computer-implemented image classification method executed by a computer, comprising: obtaining an image using the computer; processing the image, using the computer, to calculate a gradient variation magnitude difference between at least two regions of the image; determining the image is a landscape image when the gradient variation magnitude difference is less than a second predefined value; and determining the image is a close-up image when the gradient variation magnitude difference is not less than the second predefined value; wherein the gradient variation magnitude difference is calculated using the steps of: generating a reference image according to the image; dividing the image and the reference image into a plurality of blocks; respectively calculating a gradient variation in the respective blocks of the image and the reference image; calculating a gradient variation magnitude for the respective block according to the gradient variation of the corresponded blocks respectively in the image and the reference image; segmenting the image into two regions; mapping each pixel of the image to the blocks to obtain the corresponding gradient variation magnitude; averaging the gradient variation magnitude of pixels in the respective regions; and calculating the gradient variation magnitude difference of the two regions according to the average gradient variation magnitudes of the two regions.