TY - JOUR
T1 - Singular-value decomposition for through-focus imaging systems
AU - Burvall, Anna
AU - Barrett, Harrison H.
AU - Dainty, Christopher
AU - Myers, Kyle J.
PY - 2006/10
Y1 - 2006/10
N2 - Singular-value decomposition (SVD) of a linear imaging system gives information on the null and measurement components of object and image and provides a method for object reconstruction from image data. We apply SVD to through-focus imaging systems that produce several two-dimensional images of a three-dimensional object. Analytical expressions for the singular functions are derived in the geometrical approximation for a telecentric, laterally shift-invariant system linear in intensity. The modes are evaluated numerically, and their accuracy confirmed. Similarly, the modes are derived and evaluated for a continuous image representing the limit of a large number of image planes.
AB - Singular-value decomposition (SVD) of a linear imaging system gives information on the null and measurement components of object and image and provides a method for object reconstruction from image data. We apply SVD to through-focus imaging systems that produce several two-dimensional images of a three-dimensional object. Analytical expressions for the singular functions are derived in the geometrical approximation for a telecentric, laterally shift-invariant system linear in intensity. The modes are evaluated numerically, and their accuracy confirmed. Similarly, the modes are derived and evaluated for a continuous image representing the limit of a large number of image planes.
UR - https://www.scopus.com/pages/publications/33751245556
U2 - 10.1364/JOSAA.23.002440
DO - 10.1364/JOSAA.23.002440
M3 - Article
AN - SCOPUS:33751245556
SN - 1084-7529
VL - 23
SP - 2440
EP - 2448
JO - Journal of the Optical Society of America A: Optics and Image Science, and Vision
JF - Journal of the Optical Society of America A: Optics and Image Science, and Vision
IS - 10
ER -