1. A method for training a neural network to perform assessments of image quality, the method comprising: inputting into the neural network at least one set of images, each set comprising an image and at least one degraded version of the image; performing in a comparative layer a comparative ranking of each image in the at least one set of images by implementing a sigmoid function to provide pairwise ranking of the images within each set of images, the sigmoid function comprising: h ⁡ ( y i , y j ) = 1 1 + ⅇ l i · j ⁡ ( y i - y j ) wherein, y i and y j represent output quality scores associated with input images, x i and x j , respectively; and l i,j represents prior information for pairwise ranking of y i and y j output by the comparative layer; and training the neural network with the ranking information.