TY - GEN
T1 - Novel methods in denoising, resolution enhancement and object reconstruction of multidimensional signals
AU - Ponomaryov, Volodymyr I.
PY - 2013
Y1 - 2013
N2 - The presence of noise produces deficiencies during acquisition, broadcast or storage of the color image sequences [1-7]. A principal problem here consists in a design of the noise reduction techniques while image content (edges, fine details, chromaticity characteristics, etc.) should be unchanged. There are many filters designed that are based on order statistics technique, on fuzzy logic theory, etc. [1-8]. The proposed technique in difference to other state-of-the-arts approaches employs the RGB channels data and fuzzy logic description of semantic properties of image features, processing several pixel gradients together in two temporal neighboring frames. A 3×3 sliding window located into a bigger 5×5 window novel framework is employed [6] in an approach, applying the gradient values for neighboring pixels in eight different directions γ = (NW, N, NE, E, SE, S, SW, W) with respect to a central pixel. Two hypothesizes are resolved: the central pixel is a noisy or it is a free-noise pixel. The LARGE and SMALL fuzzy sets are introduced with an objective to estimate the noise contamination employing the Gaussian membership functions [6, 8] for membership degrees of gradient values.
AB - The presence of noise produces deficiencies during acquisition, broadcast or storage of the color image sequences [1-7]. A principal problem here consists in a design of the noise reduction techniques while image content (edges, fine details, chromaticity characteristics, etc.) should be unchanged. There are many filters designed that are based on order statistics technique, on fuzzy logic theory, etc. [1-8]. The proposed technique in difference to other state-of-the-arts approaches employs the RGB channels data and fuzzy logic description of semantic properties of image features, processing several pixel gradients together in two temporal neighboring frames. A 3×3 sliding window located into a bigger 5×5 window novel framework is employed [6] in an approach, applying the gradient values for neighboring pixels in eight different directions γ = (NW, N, NE, E, SE, S, SW, W) with respect to a central pixel. Two hypothesizes are resolved: the central pixel is a noisy or it is a free-noise pixel. The LARGE and SMALL fuzzy sets are introduced with an objective to estimate the noise contamination employing the Gaussian membership functions [6, 8] for membership degrees of gradient values.
UR - http://www.scopus.com/inward/record.url?scp=84888612531&partnerID=8YFLogxK
U2 - 10.1109/MSMW.2013.6622160
DO - 10.1109/MSMW.2013.6622160
M3 - Contribución a la conferencia
AN - SCOPUS:84888612531
SN - 9781479910663
T3 - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
SP - 583
EP - 586
BT - Proceedings - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
T2 - 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, MSMW 2013
Y2 - 23 June 2013 through 28 June 2013
ER -