PSF estimation by gradient descent fit to the ESF

Citation data:

Proceedings of SPIE - The International Society for Optical Engineering, ISSN: 0277-786X, Vol: 6059, Page: 60590E-60590E-9

Publication Year:
Usage 500
Downloads 462
Abstract Views 38
Captures 23
Readers 23
Citations 14
Citation Indexes 14
Repository URL:
Elisa H. Barney Smith; Luke C. Cui; Yoichi Miyake
SPIE-Intl Soc Optical Eng
Materials Science; Physics and Astronomy; Computer Science; Mathematics; Engineering; spatial attribute characterization; point spread function; edge spread function; kurtosis factor; Electrical and Computer Engineering
conference paper description
Calibration of scanners and cameras usually involves measuring the point spread function (PSF). When edge data is used to measure the PSF, the differentiation step amplifies the noise. A parametric fit of the functional form of the edge spread function (ESF) directly to the measured edge data is proposed to eliminate this. Experiments used to test this method show that the Cauchy functional form fits better than the Gaussian or other forms tried. The effect of using a functional form of the PSF that differs from the true PSF is explored by considering bilevel images formed by thresholding. The amount of mismatch seen can be related to the difference between the respective kurtosis factors. © 2006 SPIE-IS&T.