Title :
Image Registration of Very Large Images via Genetic Programming
Author :
Chicotay, Sarit ; David, Omid E. ; Netanyahu, Nathan S.
Author_Institution :
Dept. of Comput. Sci., Bar-Ilan Univ., Ramat-Gan, Israel
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 specialized transformations that should yield accurate registration of very large images.
Keywords :
genetic algorithms; image registration; GP-based approach; genetic programming; image registration; specialized transformations; transformation model; very large images; Biological cells; Educational institutions; Image registration; Optimization; Search problems; Sociology; Statistics; Image registration; genetic programming;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
DOI :
10.1109/CVPRW.2014.56