Generalized architecture of an MTANN (a class of PML) consisting of an ML model (e.g., linear-output ANN regression and support vector regression) with subregion input and single-pixel output. All pixel values in a subregion extracted from an input image are entered as input to the ML model. The ML model outputs a single pixel value for each subregion, the location of which corresponds to the center pixel in the subregion. Output pixel value is mapped back to the corresponding pixel in the output image.
