1. A method for generating one or more denoising filters comprising: receiving, by a device comprising at least one processor, at least one pair of training images, wherein the at least one pair of training images comprises a noisy and a clean training digital image; training, by the device, a denoising algorithm and associated Active Random Field model to determine denoising filters, wherein the training comprises: applying, by the device, the denoising algorithm to the at least one pair of training images, wherein the denoising algorithm comprises at least one current denoising filter; changing, by the device, at least one element in the at least one current denoising filter to produce one or more subsequent denoising filters based at least in part on a loss function, the loss function maximized by an optimization method; applying, by the device, the one or more subsequent denoising filters to the at least one pair of training images starting with one iteration and adding filters and iterations; and terminating, by the device, training upon reaching a predetermined metric of improvement; and storing, by the device, the denoising filters in a memory device.