Thoughts on standardization of parameters for image evaluation

Abstract

Images received for image processing and analysis are obtained from a wide variety of sources and with a wide variety of sensors. Because it is desirable to have image processing algorithms be as universally applicable as possible, they should be designed, where possible, to be insensitive to the parametric variations of the source material. Where this is not possible, these variations must be taken into account. Therefore, it is necessary to consider what parameters may be defined in common across a suite of image types. Objective parameters or measurements of images which, in the proper combinations, may serve as surrogates for real images may be pixel-specific, location dependent, or combinations thereof. Parameters which have proven useful in defining the characteristics of images include the gray scale linearity, granularity of the quantization, spectral content, geometrical fidelity, resolution of the system expressed as either the point spread function or the modulation transfer function, and the spatial frequency content and characteristics of the data itself.