ANALISIS PERBANDINGAN METODE FILTER MEAN, MEDIAN, MAXIMUM, MINIMUM, DAN GAUSSIAN TERHADAP REDUKSI NOISE GAUSSIAN, SALT&PAPPER , SPECKLE, POISSON, DAN LOCALVAR

I Gede Aris Gunadi

Abstract


Due to the influence of noise on an image, the image will experience a decrease in quality.  If the type of noise is known for certain, then the right solution can be determined to restore the condition of an image so that the condition returns to normal. The effort to restore the image condition is stated by image restoration. The most important thing in image restoration is determining the type of noise and the solution for the noise.

In this study several types of noise were tried,  gaussian, salt & paper, speckle, poisson, and Localvar on several image samples. In the image that had been exposed to noise, repairs were carried out with several types of filters including gaussian, mean, median, maximum, and minimum. Next was the quality of noise reduction with each filter  determined based on the value of PSNR and MSE. The results of image restoration experiments showed that the mean filter was the best filter used to improve noisegaussian, salt & peppers and speckle image quality. The median filter is the filter that is best used to improve image quality with poisson and localvar noise types.

 

 


Keywords


Image Restoration, Filtering, Noise, PSNR, MSE

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DOI: http://dx.doi.org/10.30646/sinus.v17i1.392

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