DocumentCode :
228474
Title :
Periodic noise recognition and elimination using RFPCM clustering
Author :
Dutta, Souradeep ; Mallick, Arijit ; Roy, Sourya ; Kumar, Utkarsh
Author_Institution :
Dept. of Instrum. & Electron. Eng., Jadavpur Univ., Kolkata, India
fYear :
2014
fDate :
13-14 Feb. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Frequency domain filtering is a conventional method in eliminating periodic noise in an image. Conventional methods include filtering via bandpass filter and notch filter for detecting both periodic and quasi-periodic noise in an image. In this paper, RFPCM clustering has been used to detect periodic noise spikes in Fourier amplitude domain. Qualitative and comparative analysis has been presented in this paper for clustered mask method and the conventional method as well. PSNR values of the resultant images are taken as filtering quality factor and comparison analysis is taken with respect to this value.
Keywords :
discrete Fourier transforms; filtering theory; image denoising; pattern clustering; Fourier amplitude domain; RFPCM clustering; clustered mask method and; noise elimination; periodic noise recognition; periodic noise spike detection; Clustering algorithms; Digital images; Electronic mail; Fourier transforms; Frequency-domain analysis; PSNR; Frequency domain filtering; PSNR; clustering; fourier amplitude domain; periodic noise; rough fuzzy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and Communication Systems (ICECS), 2014 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-2321-2
Type :
conf
DOI :
10.1109/ECS.2014.6892633
Filename :
6892633
Link To Document :
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