E-spline sampling for precise and robust line-edge extraction
Akira Hirabayashi, Pier Luigi Dragotti · 2010
We propose a line-edge extraction algorithm using E-spline functions as a sampling kernel. Our method is capable of extracting line-edge parameters, including amplitude, orientation, and offset, not only at sub-pixel level but also exactly provided noiseless pixel values. Even in noisy scenario, simulation results show that the proposed method outperforms a similar one based around B-spline functions with gains in standard deviation of 1.86dB for the orientation and 9.64dB for the offset when SNR is 10dB. We also show by simulations that our method extracts line-edges more precisely than the Hough transform.