TRIANGLE FUZZY TRANSFORM BASED AUTOMATIC NOISE AND COLOR IMAGE REDUCTION METHODS

Year 2018, , 168 - 178, 29.12.2018

Türker Tuncer

https://doi.org/10.36222/ejt.457053

Cited By: 1

Abstract

Noise reduction and image reduction are very important
research area for image processing and computer vision. Many papers have been
proposed for noise and image reduction. In this paper, novel triangle fuzzy
sets transform (F-transform) is proposed for color image denoising and
reduction. The proposed methods consist of histogram extraction, threshold
points calculation, fuzzy sets construction and fuzzy tansformation phases. Firstly,
histogram of the image are extracted, maximum points of histogram are
calculated, and these points are considered as threshold points. Fuzzy sets are
created using threshold points. Then, F-transform is applied on the overlapping
and non-overlapping blocks of the images for image denoising and reduction
respectively. The main objective of the presented method are to remove random
noises of the images and color image reduction with satisfactory visual quality.
In order to evaluate triangle fuzzy sets based F-transform applications,
variable noise intensities and block sizes are used. Mean absolute error (MEA),
peaks signal noise-to-ratio (PSNR) and penalized function (PEN) are utilized
for obtaining numerical results. Numerical simulations and comprasions clearly
illustare that the proposed triangle F-transform is good transformation for
random noises removing and image reduction.

Keywords

Triangle fuzzy transform, Image denoising, Image reduction, Image processing

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