Modelling reconstruction quality of Lissajous undersampled atomic force microscopy images

The reconstruction quality which can be obtained using compressive sensing depends on a number of elements. In the present paper, we establish performance indicators and use these to model the reconstruction quality of atomic force microscopy images undersampled with Lissajous sampling patterns. For this purpose, we consider previously proposed performance indicators. Furthermore, we propose new performance indicators based on the relative energy of the subsampled dictionary matrix atoms. Through extensive simulations, multiple affine models are evaluated in terms of modified coefficients of determination. The results show that the proposed performance indicators are highly correlated with the average reconstruction quality. In conclusion, the proposed performance indicators can be used to model reconstruction quality for the given application, and the proposed model outperforms the previously established model.