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Image rectification is a transformation process used to project two-or-more images onto a common image plane. This process has several degrees of freedom and there are many strategies for transforming images to the common plane. *It is used in computer stereo vision to simplify the problem of finding matching points between images (i.e. the correspondence problem). *It is used in geographic information systems to merge images taken from multiple perspectives into a common map coordinate system. == Image Rectification in Computer Vision== Stereo vision uses triangulation based on epipolar geometry to determine distance to an object. More specifically, binocular disparity is the process of relating the depth of an object to its change in position when viewed from a different camera, given the relative position of each camera is known. With multiple cameras it can be difficult to find a corresponding point viewed by one camera in the image of the other camera (known as the correspondence problem). In most camera configurations, finding correspondences requires a search in two-dimensions. However, if the two cameras are aligned correctly to be coplanar, the search is simplified to one dimension - a horizontal line parallel to the line between the cameras. Furthermore, if the location of a point in the left image is known, it can be searched for in the right image by searching left of this location along the line, and vice versa (see binocular disparity). Image rectification is an equivalent (and more often used〔) alternative to perfect camera alignment. Even with high-precision equipment, image rectification is usually performed because it may be impractical to maintain perfect alignment between cameras. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「image rectification」の詳細全文を読む スポンサード リンク
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