Modified Geometric Mean as an Estimator of Outlier based Artifacts in Natural Images

Navya, B; Sridevi, J; Vasanth, K.

doi:10.1109/icosec54921.2022.9951924

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…MEAN DET [42], MEDIAN DET [42], MDBUTMF DET [38], MDBUTMPF DET [40], VARIENTS DET [30], WINMEAN DET [6], WINMEDIAN DET [35], WINVARIENTS DET [39], and GEOMEAN DET [41] are the existing methods used for the comparison. Testing of the suggested algorithm's quality is done on a variety of Images, including those of Lena, Zebra, Boat, Cameraman, etc (Images are chosen as per the details of the image).…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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Thresholding Based Decision based Algorithm for the removal of Impulsive Artifacts in Images

Vasanth¹,

Sridevi²,

Prasad

2023

Preprint

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A Novel modified trimmed Trimean filter method is suggested for the elimination of random and impulse noise as well as the clearing of various sorts of artefacts from the standard images. The suggested filter first divides the pixels into noisy and non-noisy categories before updating the noisy pixels with trimmed modified trimean and leaving the non-noisy pixels unmodified. On a Standard image database, exhaustive tests were run, and the performance of the suggested filter was assessed in terms of both quantitative and qualitative results using the current algorithm. The suggested method was discovered to have great noise suppression capabilities by maintaining the fine details of the image even at increasing noise densities.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The suggested algorithm starts with a 3*3-pixel size. The modified used in this proposed filter will serve as a measure of central tendency to determine whether the treated pixel is damaged [41]. If a processed pixel is contaminated, noise is additionally tested in the neighborhood's median.…”

Section: Literature Surveymentioning

confidence: 99%

Thresholding Based Decision based Algorithm for the removal of Impulsive Artifacts in Images

Vasanth¹,

Sridevi²,

Prasad

2023

Preprint

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Exploring computational methods in the statistical analysis of imprecise medical data: between epistemology and ontology

Nieto Sánchez,

Bravo Valero

2024

Salud, Ciencia y Tecnología

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The accuracy of the results is essential to evaluate the effectiveness of statistical methods in the analysis of medical data with uncertainty. Indicators such as margin of error, percent agreement and coefficient of determination quantified accuracy under epistemic and ontological uncertainty. The stability of the methods was assessed by variation in trend analysis, sensitivity to small variations and model robustness. Data reliability focused on the selection of methods that effectively handle epistemic uncertainty, recording assumptions, sensitivity analysis and internal consistency. Ontological imprecision was quantified using the fuzzy membership degree and the overlap coefficient. The exploration of computational methods underlined the importance of accuracy and the handling of epistemic and ontological uncertainty, ensuring reliable results. The geometric mean filter, with a score of 0,7790, stood out as the best for its accuracy and ability to effectively handle uncertainty

show abstract

Modified Geometric Mean as an Estimator of Outlier based Artifacts in Natural Images

Cited by 2 publications

References 11 publications

Thresholding Based Decision based Algorithm for the removal of Impulsive Artifacts in Images

Thresholding Based Decision based Algorithm for the removal of Impulsive Artifacts in Images

Exploring computational methods in the statistical analysis of imprecise medical data: between epistemology and ontology

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