can i decompose image deblurring model?
In principle you can do that. You should, however, note that the two noise signals (both of which you called $n(x,y)$) are of course not identical. The two models are

$$g(x,y)=h(x,y)*f(x,y)+n(x,y)\\
g(x,y)=h(x,y)*\left[ f(x,y)+z(x,y)\right]$$

where the two noise components $n(x,y)$ and $z(x,y)$ have different properties. So you have to be careful with methods that assume certain noise properties. E.g. if it is assumed that $n(x,y)$ is white, then $z(x,y)$ is not white anymore and this has to be taken into account in the noise removal algorithm. The basic question you have to ask yourself is what you gain by changing the model.