The purpose of NIPY is to make it easier to do better brain imaging research. We believe that neuroscience ideas and analysis ideas develop together. Good ideas come from understanding; understanding comes from clarity, and clarity must come from well-designed teaching materials and well-designed software. The software must be designed as a natural extension of the underlying ideas.
Image alignment is the process of matching one image called template (let's denote it as T) with another image, I (see the above figure). There are many applications for image alignment, such as tracking objects on video, motion analysis, and many other tasks of computer vision. In 1981, Bruse D. Lucas and Takeo Kanade proposed a new technique that used image intensity gradient information to search for the best match between a template T and another image I. The proposed algorithm has been widely used in the field of computer vision for the last 20 years, and has had many modifications and extensions. One of such modifications is an algorithm proposed by Simon Baker, Frank Dellaert, and Iain Matthews. Their algorithm is much more computationally effective than the original Lucas-Kanade algorithm.