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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Kornkamol Thakulsukanant
Assumption University of Thailand
Computer Science & IT Electrical & Electronics Engineering

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A novel elementary spatial expanding scheme form on SISR method with modifying Geman&McClure function Darun Kesrarat; Kornkamol Thakulsukanant; Vorapoj Patanavijit
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.12799

Abstract

Because of the feasible and impressive fallout, the classical Super-Resolution Reconstruction (SRR) is the contemporary algorithm for improving spatial information and reducing noise and SISR (Single-Image Super-Resolution) method, which is form on the classical SRR, is solely developed for improving spatial information. Disastrously, deficiency of the classical SISR method is conceptually computed from three specifications (b, h, k) and the simulating calculation of the optimized specifications for interpolating the better and higher spatial information images with highest PSNR is so burdersome. For figuring out this issue, the Geman&Mcclure function is proposed to replace with the ordinary SISR function because this function is conceptually computed from only one specification (T), contrary to three specifications similar to classical SISR method hence this analytic article focuses to offer a novel elementary spatial expanding scheme form on SISR method with modifying Geman&Mcclure function. Therefore, the fallout of a proposed spatial expanding scheme approximately matches to classical SISR method. From these reason, a novel elementary spatial expanding scheme is easily implemented for real works.
The novel noise classification techniques found on quadruple threshold statistical detection filter under fix intensity impulse outlier environment Vorapoj Patanavijit; Kornkamol Thakulsukanant
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3105

Abstract

Because of the enormous necessity of contemporary noise suppressing algorithms, this article proposes the novel noise classification technique found on QTSD filter improved from the TTSD filter. The four thresholds for each auxiliary situations are incorporated into the proposed QTSD framework for dealing with the limitation of the earlier noise classification technique. The mathematical pattern is modeled by each photograph elements and is investigated in contradiction to the 1st threshold for analyzing whether it is non-noise or noise photograph elements. Subsequently, the calculated photograph element is analyzed with the contradiction between the 2nd threshold, which is modeled by using the normal distribution (mean and variance), and is analyzed with the contradiction between the 3rd threshold, which is modeled by using the quartile distribution (median). Finally, the calculated photograph element is investigated in contradiction to the 4th threshold, which is modeled from maximum or minimum value for analyzing whether it is non-noise or noise photograph elements FIIN. For performance evaluation, extensive noisy photographs are made up of nine photographs under FIIN environment distribution, which are synthesized for investigating the proposed noise classification techniques found on QTSD filter in the objective indicators (noise classification, non-noise classification and overall classification correctness). From these results, the proposed noise classification technique can outstandingly produce the higher correctness than the earlier noise classification techniques.
An innovative vigorous outlier recognition placed on LROAD for fix-amplitude impulsive noise Vorapoj Patanavijit; Kornkamol Thakulsukanant
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.4168

Abstract

Due to large current applications on digital images in these recent years, outlier suppression is one of the primary stages for modern computer vision implementations thereupon there are tremendously invented for creating an efficient and practical outlier suppression, which ordinarily are composed of outlier recognition stage and outlier rebuilt stage. The localised rank ordered difference (LROAD) approach, which is progressed from rank-ordered absolute differences (ROAD), has been invented since 2016. Later, the LROAD approach evolved to be one of the efficient outlier recognition stages from its eminent effectiveness. The paper focus to propose the innovative vigorous outlier recognition placed on localised rank-ordered logarithmic differences (LROLD) approach, which is progressed from LROAD and rank-ordered logarithmic differences (ROLD), which is higher effectiveness than the ordinary LROAD, for applying on FAIN. From the computer experiments, which are examined on many depictions such as Girl, Pepper F16 and Lena, the innovative vigorous outlier recognition placed on LROLD approach has higher eminent effectiveness then the stage-of-art approach such as LROAD and ROAD approaches at numerous consistencies of FAIN.
A computational experimental of noise suppressing technique stand on hard decision threshold dissimilarity Vorapoj Patanavijit; Kornkamol Thakulsukanant
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp144-156

Abstract

Due to the extreme insistence for digital image processing, plentiful modern noise suppressing techniques are embodied of dissimilarity process and suppressing process. One of the extreme capability dissimilarity is hard decision threshold (HDT) dissimilarity, which has been recently declared in 2012, for suppressing the impulsive noisy photographs thus the computer experimental statement attempts to investigate the capability of the noise suppressing technique that is stand on HDT dissimilarity for the processed photographs, which are corrupted by fixed-intensity impulse noise (FIIN). This paper proposes the noise suppressing technique stand on HDT dissimilarity for FIIN. There are 3 primary contributions of this paper. The first contribution is the statistical average of the HDT dissimilarity of noise-free elements, which are computed from plentiful ground-truth photographs by varying window size for the best HDT window size. The second contribution is the statistical average of the HDT dissimilarity of corrupted elements, which are computed from plentiful corrupted photographs by varying outlier density for the best HDT window size. The final contribution is the statistical interrelation of the capability of the noise suppressing technique and hard consistent of HDT dissimilarity are investigated by varying the outlier denseness for the best HDT hard consistence.
Co-Authors Darun Kesrarat Vorapoj Patanavijit