4.3 Determine Focal Spot, Condition : Unknown Real Im- age When the real sharp image is not known, we are faced with the problem of finding the focal spot shape i.e. PSF from only the output blurred image. This leads to the concept of blind deconvolution. Since, the process of blind deconvolution has been a heavy mathematical problem with various uncertainties, we try to approximate the ideal real image with the information obtained from blurred image or images. If we are trying to approximate the real image from a given output image, we can use the known components of the image to approximate a real image. Figure 4.5 shows the three different flows to obtain the focal spot image from the blurred image.
4.3.1 Approximate Real Image by Converting
*…show more content…*

From the blurry image edge, we predict the sharp step edge by propagating the mean minimum and maximum values along the edge. To predict a sharp edge, the function travels along an edge normal and finds the first pixel which is less than 95 percent of the previous pixel. The maximum pixel value is then calculated by taking the mean of all pixels that are within 10 percent of the initial maximum value. For the minimum value along the edge normal, choose the pixel value which is 95 percent greater than the previous pixel value. The minimum value is then the mean of all the values along the normal that is within 10 percent of the initial minimum. The values along the normal of the edge are then propagated to the minimum and maximum value to form a step edge. This process is repeated for each edge normal, thus obtaining a real sharp image. Once the real image is obtained, the focal spot profile can be obtained by deconvolution techniques mentioned earlier in the section 4.2.3.The focal spot image obtained by deconvolving a blurred image with a sharp image approximated by converting each blurred edge to a step edge is shown in figure 4.7. The focal spot image obtained by deconvolving a blurred image with a sharp

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