Thesis (PDF) - Signal & Image Processing Lab

6.4. APPLICATION EXAMPLES 105
6.4.3 Initial step for dust and scratch removal
Another example uses opening by reconstruction as an initial step for an application
that removes dust and scratches from images. The elements that remain after filtering
by the opening by reconstruction are completely preserved, including their edges. The
elements that are removed by the opening by reconstruction are completely removed,
including their edges. This feature enables one to catch candidates for dust and
scratch during the initial step. The output of the initial step is a top-hat (TH) filter
that includes all details that were filtered out by opening by reconstruction (OR)
from the original image Ioriginal, and is given by: T H = Ioriginal − OR(Ioriginal). Later
steps of the application can make further analysis of that image in order to decide
which object is dust or scratch and which is not. Afterward, objects that are dust or
scratch, according to decision rule, are removed from the image.
We have compared different methods for this application. The comparison was
done using the energy level of the top-hat image and qualitative evaluation of the
extent of dust and scratch removal. As the energy level of the top hat image is lower,
and as the dust and scratch removal is better, so the filter is declared to be more
efficient. The energy is defined by equation (6.5).
�
�
Enrg = �f�2 = f(i, j) 2 (6.5)
i,j∈f
Where f is the image and Enrg is the image energy level.
We used averaging and median filters for comparison. Table 6.2 summarizes the
energy levels of the top-hat images. Figures from 6.39 until 6.42 show top-hat images
for different structuring elements and image magnifications. The objects in the top-
hat images are the potential candidates for dust and scratch for the later steps of the
application.
For all structuring elements, the averaging filter catches all the edges of the image.
In addition, the energy of the top-hat image is higher for the averaging filter than
for the other filters listed in Table 6.2. This means that the averaging filter catches
too many candidates for dust and scratch. Therefore, it is less suitable for dust and
scratch removal application, than the other compared filters.
For a given image, the energy is higher for the median than for the filter based