1. An image processing method, the method comprising: dividing each training image of a dataset of training images into a plurality of training images patches; applying an image processing algorithm, over a range of possible tuning parameters, to each of the plurality of training image patches to generate a plurality of performance curves; constructing a loss function based upon the plurality of performance curves; training a convolutional neural network (CNN) to optimize the loss function to establish a trained convolutional neural network; predicting a specific tuning parameter for an image of interest using the trained convolutional neural network; and performing image processing of the image of interest using the specific tuning parameter and the image processing algorithm to generate a processed image of interest.