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A Canonical Image Set for Examining and Comparing Image Processing Algorithms

Jeffrey Uhlmann
University of Missouri-Columbia, 201 Naka Hall, Columbia, MO 65211, USA

Abstract—The purpose of this paper is to introduce a set of four test images containing features and structures that can facilitate effective examination and comparison of image processing algorithms. More specifically, the images are designed to more explicitly expose the characteristic properties of algorithms for image compression, virtual resolution adjustment, and enhancement. This set was developed at the Naval Research Laboratory (NRL) in the late 1990s as a more rigorous alternative to Lena and other images that have come into common use for purely ad hoc reasons with little or no rigorous consideration of their suitability. The increasing number of test images appearing in the literature not only makes it more difficult to compare results from different papers, it also introduces the potential for cherry-picking to influence results. The key contribution of this paper is the proposal to establish some canonical set to ensure that published results can be analyzed and compared in a rigorous way from one paper to another, and consideration of the four NRL images is proposed for this purpose.

Index Terms—test images, image compression, image superresolution, image enhancement, image processing

Cite: Jeffrey Uhlmann, "A Canonical Image Set for Examining and Comparing Image Processing Algorithms," Journal of Image and Graphics, Vol. 6, No. 2, pp. 137-144, December 2018. doi: 10.18178/joig.6.2.137-144

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