- author = "Sarit Chicotay and Omid E. David and Nathan S. Netanyahu",
- booktitle = "IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2014)",
- title = "Image Registration of Very Large Images via Genetic Programming",
- year = "2014",
- month = jun,
- pages = "329--334",
-
abstract = "Image registration (IR) is a fundamental task in image
processing for matching two or more images of the same
scene taken at different times, from different
viewpoints and/or by different sensors. Due to the
enormous diversity of IR applications, automatic IR
remains a challenging problem to this day. A wide range
of techniques has been developed for various data types
and problems. These techniques might not handle
effectively very large images, which give rise usually
to more complex transformations, e.g., deformations and
various other distortions.
In this paper we present a genetic programming (GP) based approach for IR, which could offer a significant advantage in dealing with very large images, as it does not make any prior assumptions about the transformation model. Thus, by incorporating certain generic building blocks into the proposed GP framework, we hope to realize a large set of specialised transformations that should yield accurate registration of very large images.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/CVPRW.2014.56",
- notes = "Also known as \cite{6910002}",
