The hit-or-miss transform (HMT) is a fundamental operation on binary images, widely used since 40 years. As it is not increasing, its extension to grey-level images is not straightforward, and very few authors have considered it. Moreover, despite its potential usefulness, very few applications of the grey-level HMT have been proposed until now. Part I of this paper, developed hereafter, is devoted to the description of a theory leading to a unification of the main definitions of the grey-level HMT, mainly proposed by Ronse and Soille, respectively (part II will deal with the applicative potential of the grey-level HMT, which will be illustrated by its use for vessel segmentation from 3D angiographic data). In this first part, we review the previous approaches to the grey-level HMT, especially the supremal one of Ronse, and the integral one of Soille; the latter was defined only for flat structuring elements (SEs), but it can be generalized to non-flat ones. We present a unified theory of the grey-level HMT, which is decomposed into two steps. First a fitting associates to each point the set of grey-levels for which the SEs can be fitted to the image; as in Soille’s approach, this fitting step can be constrained. Next, a valuation associates a final grey-level value to each point; we propose three valuations: supremal (as in Ronse), integral (as in Soille) and binary.