TY - GEN
T1 - High density impulse noise removal by Fuzzy Mean Linear Aliasing Window Kernel
AU - Utaminingrum, Fitri
AU - Uchimura, Keiichi
AU - Koutaki, Gou
PY - 2012
Y1 - 2012
N2 - Fuzzy Mean Linear Aliasing Window Kernel (FMLAWK) filter method proposed to reducing the high-density impulse noise interference and generating the smooth image performance. FMLAWK filter is a spatial filter, which combined from fuzzy method and Linear Aliasing Filter (LAF). The initial step is finding the degree of membership function (μ) value of each matrix element on the corrupted image which use the fuzzy method. Furthermore, the μ value of the corrupted image processed by LAF method which using 3×3 window. The reducing of 3×3 windows on LAF process will be obtain one pixel data based on Linear method. Our research also provides kernel algorithms. Preprocessing Kernel algorithm used for checking of each element matrix on the 3×3 window. If the matrix element contaminated by impulse noise, so the matrix element replaced with a new element data. Our simulation result shows the image filtering better and smoother quality than the comparison method.
AB - Fuzzy Mean Linear Aliasing Window Kernel (FMLAWK) filter method proposed to reducing the high-density impulse noise interference and generating the smooth image performance. FMLAWK filter is a spatial filter, which combined from fuzzy method and Linear Aliasing Filter (LAF). The initial step is finding the degree of membership function (μ) value of each matrix element on the corrupted image which use the fuzzy method. Furthermore, the μ value of the corrupted image processed by LAF method which using 3×3 window. The reducing of 3×3 windows on LAF process will be obtain one pixel data based on Linear method. Our research also provides kernel algorithms. Preprocessing Kernel algorithm used for checking of each element matrix on the 3×3 window. If the matrix element contaminated by impulse noise, so the matrix element replaced with a new element data. Our simulation result shows the image filtering better and smoother quality than the comparison method.
KW - fuzzy method
KW - impulse noise removal
KW - linear aliasing filter
UR - https://www.scopus.com/pages/publications/84869413910
U2 - 10.1109/ICSPCC.2012.6335693
DO - 10.1109/ICSPCC.2012.6335693
M3 - Conference contribution
AN - SCOPUS:84869413910
SN - 9781467321938
T3 - 2012 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012
SP - 711
EP - 716
BT - 2012 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012
T2 - 2012 2nd IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012
Y2 - 12 August 2012 through 15 August 2012
ER -