Given an $m \times n$ matrix $A$ and a vector $c \in \mathbb R^n$, define $\eta(A,c) \ge 0$, $$ \eta(A,c) := \sup_{u \in \mathbb R^n} u^\top c - \frac{1}{2}\|u\|^2 - \|Au\|. $$ Note that $\eta(A,c) = \|c\|^2/2 - M_f(c)$, where $M_f(c) := \min_{u \in \mathbb R^n}\dfrac{1}{2}\|u-c\|^2 + \|Au\|$ defines the Moreau envelope of the function $f(x):=\|Ax\|$ at the point $c$.
Question. What is an analytic formula for $\eta(A,c)$, perhaps by means of the singular-values of $A$ ?
(If it helps, it may be assumed that $m=n$ and $A$ is positive-definite).
Upper and lower-bounds
If $\sigma_\min(A)$ is the least singular-value of $A$ and $\sigma_\max(A)$ is its largest singular-value (i.e is operator norm), then, it is clear that $$ \eta(\sigma_\max(A) I_m,c) \le \eta(A,c) \le \eta(\sigma_\min(A) I_m,c). $$
One the other hand, a simple calculation reveals that $\eta(\theta I_m,c) = \dfrac{1}{4}(\|c\|-\theta)_+^2$ for all $\theta \in \mathbb R$. Thus, $$ \frac{1}{4}(\|c\|-\sigma_\max(A))_+ \le \eta(A,c) \le \frac{1}{4}(\|c\|-\sigma_\min(A))_+^2. $$