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P‐55: Adaptive Noise Reduction Method using Variable Window Size Based on Region Analysis
Author(s) -
Lim Jae Hwan,
Cho Sung In,
Kim Young Hwan
Publication year - 2014
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/j.2168-0159.2014.tb00307.x
Subject(s) - noise reduction , noise (video) , image (mathematics) , filter (signal processing) , window (computing) , computer science , variable (mathematics) , non local means , reduction (mathematics) , image denoising , artificial intelligence , image noise , variance (accounting) , pattern recognition (psychology) , median filter , mathematics , algorithm , computer vision , image processing , mathematical analysis , geometry , accounting , business , operating system
This paper proposes a novel denoising method which uses a variable window size for noise filter depending on the results of local region analysis. The proposed method classifies local regions of a given noisy image as detail or smooth regions using a new parameter which is calculated by the ratio of estimated noise variance to local variance. The new parameter, a detail descriptor, represents the amount of image details in a local region. Then, the proposed method adaptively applies a noise reduction filter to remove image noise while preserving image details by regulating the filtering window size depending on the detail descriptor.