By A. Ardeshir Goshtasby
A definitive and finished overview of present literature and the main innovative applied sciences within the box of photograph 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
A method known as edge focusing starts by ﬁnding edges at a coarse resolution (a rather high standard deviation of Gaussian). The standard deviation of the Gaussian smoother is then gradually reduced while tracking the edges from low to high resolution. The process allows edges to accurately position themselves while avoiding weaker edges entering the picture. It has been shown that if the standard deviation of Gaussians is changed by half a pixel, the edges move by less than a pixel, except near places where edge contours break into two or more contours .
12. 12a shows the zero-crossing edges of the X-ray angiogram in Fig. 6a obtained by functional approximation. 5 pixels before determining its edges. Removing the weak edges, the image shown in Fig. 12b is obtained. The quality of edges detected by functional approximation are similar to those detected by the LoG operator. 6 Edge detection in 3-D images The procedure for detecting edges in 3-D closely follows that in 2-D. The LoG operator in 3-D is computed from LoG [f (x, y, z)] = = ∂2 ∂2 ∂2 + + ∂x2 ∂y 2 ∂z 2 ∂ 2 G(x) ∂x2 G(x, y, z) f (x, y, z) G(y) G(z) f (x, y, z) IMAGE SEGMENTATION + ∂ 2 G(y) ∂y 2 G(x) G(z) f (x, y, z) + ∂ 2 G(z) ∂z 2 G(x) G(y) f (x, y, z).
13. Edges determined by the LoG operator with a Gaussian of standard deviation 2 voxels are shown in Fig. 13b. The weakest 70% of the edges have been removed. Canny edges obtained using a Gaussian of standard deviation 2 voxels and interactively removing the weak edges are shown in Fig. 13c. 13d shows edges obtained by the intensity ratios. Again, the standard deviation of the Gaussian smoother was 2 pixels and the weak edges were interactively removed to keep the same number of edges as those found by the Canny method and the LoG operator.