Error measures can be used to numerically assess the differences betwe
en two images. Much work has been done on binary error measures, but l
ittle on objective metrics for grey-scale images. In our discussion he
re we introduce a new grey-scale measure, Delta(g), aiming to improve
upon the most common grey-scale error measure, the root-mean-square er
ror. Our new measure is an extension of the authors' recently develope
d binary error measure, Delta(b), not only in structure, but also havi
ng both a theoretical and intuitive basis. We consider the similaritie
s between Delta(b) and Delta(g) when tested in practice on binary imag
es, and present results comparing Delta(g) to the root-mean-squared er
ror and the Sobolev norm for various binary and grey-scale images. The
re are no previous examples where the last of these measures, the Sobo
lev norm, has been implemented for this purpose.