Open AccessSuppression of noise in SEM images using weighted local hysteresis smoothing filter
Author(s) -
Mazhari Mohadeseh,
Hasanzadeh Reza P. R.
Publication year - 2016
Publication title -
scanning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1932-8745
pISSN - 0161-0457
DOI - 10.1002/sca.21311
Subject(s) - smoothing , noise reduction , computer science , noise (video) , pixel , artificial intelligence , filter (signal processing) , median filter , reduction (mathematics) , thresholding , computer vision , pattern recognition (psychology) , mathematics , algorithm , image (mathematics) , image processing , geometry
Summary It has been proven that Hysteresis Smoothing (HS) has several advantages for Scanning Electron Microscopy (SEM) image noise reduction. HS uses hysteresis thresholding to remove noise besides preserving important details of images. Determination of optimal threshold values (cursor width) plays an effective role in improving the performance of HS based filters. Recently, a novel local technique, named Local Adaptive Hysteresis Smoothing (LAHS), has been proposed to compute an optimal cursor width. In this paper, a new method is proposed to improve the performance of LAHS in noise reduction and detail preservation. In the proposed approach which is based on weighted averaging, local statistical characteristics of the image are used in order to modify the final values of estimated pixels by LAHS method. Proposed method is applied to SEM images corrupted by different levels of noise. Noise reduction and detail preservation performance of the proposed method is compared in both objective and subjective manners with other HS based filters. Experimental results demonstrate that the proposed method is successful in improving the performance of LAHS and also it achieves better performance in noise reduction besides detail preservation of SEM images in comparison with other HS based filters. SCANNING 38:634–643, 2016. © 2016 Wiley Periodicals, Inc.