The invention discloses a super-resolution image processing method based on a probability generation model. The method comprises: (1), inputting an image; (2), obtaining a training sample; (3), obtaining a testing sample; (4), training a probability generation model; and (5), testing the probability generation model. According to the invention, compared with the common method, the super-resolutionimage processing method enables the generated high-resolution image to have higher resolution than that generated by the common method and to have more information; and with the prior information ofthe probability generation model and information implied by a hidden variable, the image super-resolution speed is increased. The method is a high-efficiency super-resolution image processing method.