TY - JOUR
T1 - An adaptive graininess suppression method for restoration of color degraded images
AU - Yoshimori, Seiki
AU - Mitsukura, Yasue
AU - Fukumi, Minoru
AU - Akamatsu, Norio
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Previous studies of image restoration for noise images were based on a mask processing. These conventional noise removal methods based on the mask processing have an issue of defining degradation to accompany a spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from an 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 images. Moreover, we use the canny edge detection operator with 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 demonstrated the effectiveness of the present method for the noise added images and confirmed it by means of computer simulation.
AB - Previous studies of image restoration for noise images were based on a mask processing. These conventional noise removal methods based on the mask processing have an issue of defining degradation to accompany a spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from an 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 images. Moreover, we use the canny edge detection operator with 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 demonstrated the effectiveness of the present method for the noise added images and confirmed it by means of computer simulation.
KW - Edge detection
KW - Graininess suppression
KW - Simple PCA
KW - Wiener filter
UR - http://www.scopus.com/inward/record.url?scp=72349098732&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=72349098732&partnerID=8YFLogxK
U2 - 10.1541/ieejeiss.127.2093
DO - 10.1541/ieejeiss.127.2093
M3 - Article
AN - SCOPUS:72349098732
SN - 0385-4221
VL - 127
SP - 2093-2100+19
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
IS - 12
ER -