An image processing method, comprising: obtaining a first image and a second image, wherein the first image and the second image are shot at the same time by two different image obtaining apparatuses (101, 102), which output different images, a visible light image, a near infrared image, a thermal infrared image, a multi-spectral image or a hyper-spectral image; for the first image and the second image, separately obtaining, through calculation, a gradient saliency feature map of the image; based on the gradient saliency feature maps of the first image and the second image, performing feature matching between the first image and the second image to obtain a dense disparity map of the first image; and based on the dense disparity map of the first image, performing disparity translation on a pixel in the second image corresponding to a pixel in the first image, and fusing the first image and the pixel in the second image; wherein the obtaining, through calculation, a gradient saliency feature map of the image comprises: extracting a vertical gradient and a horizontal gradient that are of each band in the image by using a gradient operator, and obtaining, through calculation based on the vertical gradient and the horizontal gradient, a gradient saliency feature map of each band in the image; and performing weighted averaging on each pixel in the gradient saliency feature map of each band to obtain a gradient saliency map of the image. obtaining a first image and a second image, wherein the first image and the second image are shot at the same time by two different image obtaining apparatuses (101, 102), which output different images, a visible light image, a near infrared image, a thermal infrared image, a multi-spectral image or a hyper-spectral image; for the first image and the second image, separately obtaining, through calculation, a gradient saliency feature map of the image; based on the gradient saliency feature maps of the first image and the second image, performing feature matching between the first image and the second image to obtain a dense disparity map of the first image; and based on the dense disparity map of the first image, performing disparity translation on a pixel in the second image corresponding to a pixel in the first image, and fusing the first image and the pixel in the second image; wherein the obtaining, through calculation, a gradient saliency feature map of the image comprises: extracting a vertical gradient and a horizontal gradient that are of each band in the image by using a gradient operator, and obtaining, through calculation based on the vertical gradient and the horizontal gradient, a gradient saliency feature map of each band in the image; and performing weighted averaging on each pixel in the gradient saliency feature map of each band to obtain a gradient saliency map of the image. extracting a vertical gradient and a horizontal gradient that are of each band in the image by using a gradient operator, and obtaining, through calculation based on the vertical gradient and the horizontal gradient, a gradient saliency feature map of each band in the image; and performing weighted averaging on each pixel in the gradient saliency feature map of each band to obtain a gradient saliency map of the image.