1. A method for processing digital image data, comprising: receiving a plurality of sets of image data representing an image at different times; extracting a first set of intensity values corresponding to a first pixel from the plurality of sets of image data, each set of image data having a corresponding time value, each intensity value in the first set being extracted from a corresponding set of image data; identifying a first subset of the first set of intensity values excluding saturation and undercut data points, the intensity values of the first subset having a substantially linear relationship with each other; performing regression on the first subset to generate a digital representation of the first pixel of the image, the regression deriving a first regression slope corresponding to the first pixel; extracting a second set of intensity values corresponding to a second pixel from the plurality of sets of image data, each intensity value in the second set being extracted from a corresponding set of image data; identifying a second subset of the second set of intensity values excluding saturation and undercut data points, the intensity values of the second subset having a substantially linear relationship with each other; performing regression on the second subset to generate a digital representation of the second pixel of the image, the regression deriving a second regression slope corresponding to the second pixel; and normalizing the first regression slope and the second regression slope by multiplying the first regression slope and the second regression slope by a normalizing value, the normalizing deriving a first relative intensity value corresponding to the first pixel and a second relative intensity value corresponding to the second pixel.