The performance of adaptive tuning piecewise cubic Hermite interpolation model for signal-to-noise ratio estimation

A technique based on the piecewise cubic Hermite interpolation (PCHI) model was previously applied to calculating the signal-to-noise ratio (SNR) in scanning electron microscope (SEM) images. An algorithm was also used by cascading the tuning technique, named adaptive tuning piecewise cubic Hermite interpolation (ATPCHIP) model. Comparisons were made with the performance of the other methods – adaptive slope nearest neighbourhood (ASNN), linear least square regression (LLSR) and nonlinear least square regression (NLLSR) through Cramer-Rao lower bound (CRLB), t-test, scatter plot and Bland-Altman plot. Using different images, the ATPCHIP single-image model is shown to be much better than other models.