Elektronika 2009-11.pdf - Instytut Systemów Elektronicznych

This image has undergone the process of scanning by two
scanners of low quality and model one. The initial values of
quality criteria between image amounted accordingly:
NMSE 0.217
MD 161
In the course of learning process of the network a filter of ratios
showed on picture no 3 was obtained.
Fig. 1. Neural network configuration
Rys. 1 Konfiguracja sieci neuronowej
The whole learning process continues according to the following
steps:
• input of an image of low quality,
• determining an error according to formula no 5,
• determining new wages according to formula no 4,
• repeating steps no 1 to 3 as long as the error becomes satisfactorily
small.
The result of the operation of the neural network is the filter
of 5 x 5 mask (25 wages), which in the course of realization
of discrete tangle operation described by formula no 3,
improve the quality of digital images acquired by low class
scanner in such a way, that they will correspond with images
from the model scanner.
Experimental research results
In this point the result of the experimental research will be presented.
For the needs of experiment, two scanners, which
construction is based on CCD matrice, were used:
• low quality scanner,
• high quality scanner - model scanner.
In the learning process of neural network, digital image
Man.bmp (Fig. 2) was used.
0.0090 0.0244 0.0369 0.0224 0.0139
0.0263 0.0588 0.0890 0.0564 0.0301
0.0544 0.0998 0.1653 0.0965 0.0570
0.0272 0.0507 0.0836 0.0549 0.0251
0.0132 0.0206 0.0369 0.0256 0.0095
Control criteria values for two images after applying linear
filtration amounted accordingly:
NMSE 0.097
MD 54
Amplitude characteristic of the filter is presented on the
Figure 3. Analyzing the values of mask ratios and looking at
amplitude characteristic of the filter it can be stated that it is
a filter of a down capacity character. It means that the disturbances
in the CCD matrice of a low class scanner mainly have
the character of noises.
To check the correctness of operation of the filter generated
by network, ten pairs of image acquired by two scanners
were examined, the results are presented in table 3 and 4.
Tabl. 3. NMSE error before and after filtration
Tab. 3. Błąd NMSE po filtracji
NMSE before filtration
NMSE after filtration
Images 1 0.217 0.097
Images 2 0.219 0.101
Images 3 0.208 0.099
Images 4 0.275 0.121
Images 5 0.215 0.089
Fig. 2. Image Man.bmp Rys. 2. Obraz Man.bmp
Fig. 3. Amplitude characteristic of the filter
Rys. 3 Charakterystyka amplitudowa filtru
26 ELEKTRONIKA 11/2009