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CLC-Conference-Proceeding-2018

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The values of the pixels of brightness or<br />

specularity reflection correspond to peaks of<br />

intensities of white in the histogram that are<br />

unreal and also do not allow the adequate<br />

inspection of the image by the doctor.<br />

In the preprocessing of these images one<br />

of the first steps is precisely the removing of the<br />

specularity reflections. To eliminate this effect it<br />

is necessary to detect the brightness pixels. Three<br />

algorithms were studied to obtain the masks<br />

(algorithms that mark the pixels). The following<br />

figure shows a colposcopy image with the<br />

brightness pixels marked.<br />

Figura 3: Mask obtained using a threshold 0.85 ∗<br />

Intmax (see xlv )<br />

Once detected and marked the pixels are<br />

removed from the image and algorithms are used<br />

that that performs a restoration approximately in<br />

those areas. Three procedures were also studied<br />

to obtain the restored image.<br />

Figura 4: Results after carrying out the<br />

restoration<br />

The results were validated qualitatively<br />

using the experience of the doctors. In the<br />

previous figure the result of one of the studied<br />

algorithms is observed.<br />

The experimentation was carried out on<br />

a set of 104 images with different appearance<br />

combining the masks and the restoration<br />

algorithms, to read about the experimentation,<br />

see xlvi . From the experimentation, 86.5% of<br />

restorations were evaluated with values greater<br />

than 2 on a scale of 2 to 5, of which 66.3% were<br />

evaluated with values greater than 3.<br />

In order to improve the results, the NMF<br />

will be applied. For that the absent data matrix<br />

containing the image information is considered<br />

like in xlvii .<br />

In xlviii a similar study is presented. In this case<br />

only gray scale images are considered. The next<br />

figure shows the missing data in the matrix.

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