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<p><strong>Abstract.</strong> The General Image Quality Equation (GIQE) is an analytical tool derived by regression modelling that is routinely employed to gauge the interpretability of raw and processed images, computing the most popular quantitative metric to evaluate image quality; the National Image Interpretability Rating Scale (NIIRS). There are three known versions of this equation; GIQE&amp;nbsp;3, GIQE&amp;nbsp;4 and GIQE&amp;nbsp;5, but the last one is scarcely known. The variety of versions, their subtleties, discontinuities and incongruences, generate confusion and problems among users. The first objective of this paper is to identify typical sources of confusion in the use of the GIQE, suggesting novel solutions to the main problems found in its application and presenting the derivation of a continuous form of GIQE&amp;nbsp;4, denominated GIQE&amp;nbsp;4C, that provides better correlation with GIQE&amp;nbsp;3 and GIQE&amp;nbsp;5. The second objective of this paper is to compare the predictions of GIQE&amp;nbsp;4C and GIQE&amp;nbsp;5, regarding the maximum image quality rating that can be achieved by image processing techniques. It is concluded that the transition from GIQE&amp;nbsp;4 to GIQE&amp;nbsp;5 is a major paradigm shift in image quality metrics, because it reduces the benefit of image processing techniques and enhances the importance of the raw image and its signal to noise ratio.</p>

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