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Image registration
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=== Intensity-based vs feature-based === Image registration or image alignment algorithms can be classified into intensity-based and feature-based.<ref name="AG">A. Ardeshir Goshtasby: [http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471649546.html 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications], Wiley Press, 2005.</ref> One of the images is referred to as the ''target'', ''fixed'' or ''sensed'' image and the others are referred to as the ''moving'' or ''source'' images. Image registration involves spatially transforming the source/moving image(s) to align with the target image. The reference frame in the target image is stationary, while the other datasets are transformed to match to the target.<ref name="AG"/> Intensity-based methods compare intensity patterns in images via correlation metrics, while feature-based methods find [[correspondence problem|correspondence]] between image features such as points, lines, and contours.<ref name="AG"/> Intensity-based methods register entire images or sub-images. If sub-images are registered, centers of corresponding sub images are treated as corresponding feature points. Feature-based methods establish a correspondence between a number of especially distinct points in images. Knowing the correspondence between a number of points in images, a geometrical transformation is then determined to map the target image to the reference images, thereby establishing point-by-point correspondence between the reference and target images.<ref name="AG"/> Methods combining intensity-based and feature-based information have also been developed.<ref name="PapademetrisJackowski2004">{{cite book|last1=Papademetris|first1=Xenophon|title=Medical Image Computing and Computer-Assisted Intervention β MICCAI 2004|last2=Jackowski|first2=Andrea P.|last3=Schultz|first3=Robert T.|last4=Staib|first4=Lawrence H.|last5=Duncan|first5=James S.|chapter=Integrated Intensity and Point-Feature Nonrigid Registration|volume=3216|year=2004|pages=763β770|issn=0302-9743|doi=10.1007/978-3-540-30135-6_93|series=Lecture Notes in Computer Science|isbn=978-3-540-22976-6}}</ref>
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