1. An image processing method, comprising: setting, by a processor, one or more initial parameters of a cellular simultaneous recurrent network (CSRN); generating, by the processor, a target image based on the one or more initial parameters; executing, by the processor, a training process for training the CSRN to learn an image processing task based on the generated target image, wherein the training process performs the image processing task on one of a plurality of sub-images of an input image; storing, on a storage device, one of the plurality of the sub-images of the input image; performing, by the processor, the training process until the image processing task has been performed on each of the plurality of sub-images of the input image; and performing, by the processor, an image transformation on the input image after the training process for training the CSRN is complete to generate an output image which is correlated to the generated target image, wherein the executing of the training process includes: creating, by the processor, a CSRN object by setting one or more random initial weights, performing, by the processor, a testing loop based on the CSRN object, performing, by the processor, a testing loop based on the CSRN object, and performing, by the processor, a result loop of the tested CSRN object when the testing loop is completed.