TY - GEN
T1 - A proposal of adaptive graininess suppression method
AU - Yoshimori, Seiki
AU - Mitsukura, Yasue
AU - Fukumi, Minoru
AU - Akamatsu, Norio
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Previous studies of image restoration for noise image were based on mask processing. These conventional noise removal methods represented from mask processing have issue of definition degradation to accompany spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from a noise image and perform graininess suppression for this image based on edge information. On the edge detection, we execute an image transformation for an image that enables us to extract edge by making principal component image. Moreover, we use the canny edge detection operator that can detect a weak edge that relates to a real edge, and do not detect a lie edge. In the suppression process, we use Wiener filter that can restore an noise image without making a complete edge map and the original signal map. We have that the present method for the noise added images to verify effectiveness and have confirmed this.
AB - Previous studies of image restoration for noise image were based on mask processing. These conventional noise removal methods represented from mask processing have issue of definition degradation to accompany spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from a noise image and perform graininess suppression for this image based on edge information. On the edge detection, we execute an image transformation for an image that enables us to extract edge by making principal component image. Moreover, we use the canny edge detection operator that can detect a weak edge that relates to a real edge, and do not detect a lie edge. In the suppression process, we use Wiener filter that can restore an noise image without making a complete edge map and the original signal map. We have that the present method for the noise added images to verify effectiveness and have confirmed this.
KW - GA
KW - Graininess suppression
KW - Image restroation
KW - SPCA
UR - http://www.scopus.com/inward/record.url?scp=50249169927&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50249169927&partnerID=8YFLogxK
U2 - 10.1109/SICE.2007.4421470
DO - 10.1109/SICE.2007.4421470
M3 - Conference contribution
AN - SCOPUS:50249169927
SN - 4907764286
SN - 9784907764289
T3 - Proceedings of the SICE Annual Conference
SP - 2827
EP - 2831
BT - SICE Annual Conference, SICE 2007
T2 - SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Y2 - 17 September 2007 through 20 September 2007
ER -