- Tytuł:
- Improving Image Sharpness by Surface Recognition
- Autorzy:
- Zerbino, D.
- Powiązania:
- https://bibliotekanauki.pl/articles/410992.pdf
- Data publikacji:
- 2019
- Wydawca:
- Polska Akademia Nauk. Oddział w Lublinie PAN
- Tematy:
-
cellular automata
image contrasting
sharpness
correct gradient
logical correction of colors
neocognitron - Opis:
-
The article proposes a rule for improving image sharpness and analyzes its implementation by means of the cellular automata formalism and neural networks. It has been proved, that the previously known contrasting algorithm, which uses a template and 3x3 pixels, can be improved considerably by repeatedly applying the iterative process over templates 2x2 with the rule "anti - blur" ( C 11 = C 11 x F - ( C 12 + C 21 + C 22) x S ) and gradient color correction at each step after the "anti - blur". Colors of images in the template are presented as real numbers (R, G, B). To correct the gradient (C11 < C12, C11 < C21, C11
- Źródło:
-
ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2019, 8, 2; 39-44
2084-5715 - Pojawia się w:
- ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
- Dostawca treści:
- Biblioteka Nauki