By A. Ardeshir Goshtasby
A definitive and finished evaluate of present literature and the main innovative applied sciences within the box of photo registration. rather well geared up and written. a must have for machine experts.
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Additional resources for 2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
23) and letting ∆x = 1, we obtain Dx [f (x, y)] = i(x + 1, y)p(x + 1, y) − i(x, y)p(x, y). 24) can be approximated by Dx [f (x, y)] = i(x, y)[p(x + 1, y) − p(x, y)]. 28) and respectively. When surface properties at (x1 , y) and (x2 , y) are the same and surface properties at (x1 + 1, y) and (x2 + 1, y) are the same also, we expect that gradients at x1 and x2 be the same. However, we see that if illuminations at (x1 , y) and (x2 , y) are different, gradients at (x1 , y) and (x2 , y) will be different too.
8b are obtained. Representing the intensities as elevations, the 3-D elevation map shown in Fig. 8c is obtained. Although ridges in this image should be detected as edges, the ridge points do not represent locally maximum gradients in the gradient direction. Therefore, when only locally maximum gradients in the gradient direction are detected, some critical edges are missed, causing a boundary contour to break. By considering locally minimum gradients that are connected from both sides to locally maximum gradients as edges, the edge contour in Fig.
The weight at a point may be set to the gradient magnitude at the point to ensure that the obtained curve passes closer to points with higher gradient magnitudes. Since images come from a variety of scanners, have different levels of noise, and are in different resolutions, the employed edge detection method should have 30 PREPROCESSING parameters that can be adjusted to these image variations. This curve-ﬁtting method has three parameters that can be varied to meet these needs. 1. The gradient threshold g, which selects the pixels in a region.