TRIANGLE FUZZY TRANSFORM BASED AUTOMATIC NOISE AND COLOR IMAGE REDUCTION METHODS

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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