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Thesis (PDF) - Signal & Image Processing Lab

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4.3. FILTERING USING A COMBINED METHOD 55<br />

4.3 Filtering using a combined method<br />

It is possible to combine the features of the above two methods into a single method.<br />

We can still look at all multiple path combinations and find such a combination that<br />

results in the largest adapted SE and a longest alternating sequence. An example is<br />

given in Fig. 4.13.<br />

4.4 Results Comparison<br />

4.4.1 Comparison of different methods for avoiding trenches<br />

In this section, we summarize the comparison between different methods for solving<br />

the trench problem. Figs. 4.14(c),(d) show the trench problem in BTV-based erosion<br />

ˆεB and opening ˆγB of the noisy image in Fig. 4.14(b), respectively. Figures 4.15, 4.16<br />

and 4.17 show the results of the three proposed methods. The multiple minimal paths<br />

method is unacceptable, because it leaves trenches. The adaptive structure element<br />

method and combined method results are very similar. The combined method results<br />

are better than those of the adaptive structuring element method, but it is more<br />

complex and more memory consuming.<br />

4.4.2 Filtering of AS images versus traditional morphological<br />

filtering<br />

In this section, filtering results in the Alternating-Sequence inf-semilattice are com-<br />

pared to the traditional erosion, dilation, opening, closing, open-close, close-open<br />

operators in the complete lattice of gray level functions and a median filter.<br />

In the example given in Fig. 4.19, traditional closing removes dark noise pixels,<br />

but not the bright ones, and damages thin dark parts and edges. Traditional opening<br />

removes bright noise, but not dark noise. In contrast, opening that was defined in<br />

inf-semilattice of AS images is self-dual and removes both bright and dark noise.<br />

However, it is possible to perform pseudo self-dual filtering in complete lattice of gray<br />

level functions using traditional open-close or close-open operators, see Fig. 4.20.<br />

The drawback is that such filtering contains two consecutive operations. Opening<br />

removes bright noise, but damages thin bright parts or edges. Closing after opening

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