马尔科夫随机场一般是离散的。当然也有连续的马尔可夫随机场，如果假设这个马尔可夫随机场定义在一个域U上面而且任意x∈U，Y(x)都是服从高斯分布的，而且两点间的covariance function K(x,y)=G(x,y)，where G是对应U的格林函数，那么这个随机场既是马尔可夫随机场，也是高斯随机场。(The Markov random field is generally discrete. Of course there are continuous Markov random field, assuming that the Markov random field defined in a domain of U and above any X in U, Y (x) are subject to Gauss distribution, and between the two covariance function K (x, y) =G (x, y), where G is the corresponding Green function U, then this is a random field Markov random field, but also with the Gauss airport.)