Download 2-D and 3-D Image Registration: for Medical, Remote Sensing, by A. Ardeshir Goshtasby PDF

By A. Ardeshir Goshtasby

A definitive and finished overview of present literature and the main leading edge applied sciences within the box of snapshot registration. rather well prepared and written. a must have for machine experts.

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Extra info for 2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications

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3 Feature Selection Image features are unique image properties that can be used to establish correspondence between two images. The most desired features are points, because their coordinates can be directly used to determine the parameters of a transformation function that registers the images. In some images it may not be possible to detect point features; however, lines or regions may be abundant. In such situations points are derived from the lines and regions. For example, the intersections of corresponding line pairs produce corresponding points and the centroids of corresponding regions produce corresponding points.

28 PREPROCESSING If a pixel is of the same distance to two or more MST vertices, it could be connected to the MST in two or more different ways. In such a situation, the pixel is connected to the MST vertex that produces the largest absolute intensity difference between the two points. Selecting MST edges in this manner will ensure that branches are connected to the spine in the direction of the maximum gradient. A complex region may have an MST that has many branches. In order to obtain longer curve segments, the maximal path (longest path) in the MST is determined.

Assuming Y (i) is the ith element of Y, g(i, j) is the ijth element of g, and f (i, j) is the ijth element of f , the following algorithm computes f given g and r. 1: Direct computation of inverse filtering 1: 2: Determine L and U. For j = 0, . . 4: 15 Set Y (0) = g(0, j). Compute Y (i) = g(i, j) − li−1 Y (i − 1) for i = 1, . . , M − 1. Set f (M − 1, j) = Y (M − 1)/buM −1 . Compute f (i, j) = [Y (i)/[b−f (i+1, j)]/ui for i = (M −2), . . , 0. Computation of each element of matrix f requires only four multiplications and divisions.

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