what is a Gaussian signal? I am learning Wiener filtering for 2D images by myself. From one book, it reads

It should be noted that the study of the more general problem of signal denoising dates
back to at least Norbert Wiener in the 1940s. The celebrated Wiener filter provides the optimal solution to the recovery of Gaussian signals contaminated by AWGN. The derivation
of Wiener filtering, based on the so-called orthogonality principle, represents an elegant solution and the only known situation where constraining to linear solutions does not render
any sacrifice on the performance. 

It mentions Gaussian signals. I know Gaussian noise. What is Gaussian signal? I cannot find the definition of Gaussian signal via google. Does it mean one signal is contaminated by Gaussian noise?
The stochastic description of signals is realized by random processes. The book you cite actually speaks of a Gaussian random process. By definition, every random variable drawn from that process has a Gaussian probabilty density function. Mathematically speaking: let $\mathbf X(n)$ be the random process representing the signal, then for every $n_1$ the random variable
$$
X=\mathbf X(n_1)
$$
is Gaussian distributed. This in turn means, that $X$ has the probability density function
$$
p_\mathrm X (x) = \frac{1}{\sqrt{2\pi\sigma^2}}\mathrm e^{-\frac{(x-\mu)^2}{2\sigma^2}},
$$
where $\mu$ and $\sigma$ are the mean and standard deviation of $X$, respectively.