Abstract
This paper presents a third-order diffusion equations-based optical image
reconstruction algorithm. The algorithm has been implemented using finite
element discretizations coupled with a hybrid regularization that combines both
Marquardt and Tikhonov schemes. Numerical examples are used to compare between
the third- and first-order reconstructions. The results show that the
third-order reconstruction codes are more stable than the first-order codes, and
are capable of reconstructing void-like regions. From the examples given, it has
also been shown that the first-order codes fail to both qualitatively and
quantitatively reconstruct the void-like regions.
©1999 Optical Society of America
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