An information handling system operating a learning dynamic gamma-correction optimization system may execute a method including identifying a combination of red, green, and blue subpixel component values for a plurality of pixels, and determining optimal red, green, and blue subpixel component values for the plurality of pixels by running a gamma correction algorithm using a gamma correction factor associated with a maximum gradient energy between the plurality of pixels. A training session for a neural network may include associating each of the red, green, and blue subpixel component values with one of a plurality of input signal node values and forward propagating the input signal node values through the neural network to output preliminary output signal node values using initial weighting values, comparing the optimal red, green, and blue subpixel component values with the preliminary output signal node values to determine error signals for each output value, determining an error signal associated with each node of the neural network by back propagating the determined error signals through the neural network, and determining a plurality of corrected weighting variables that would result in output of the optimal red, green, and blue subpixel component values.