Pelembutan Citra dengan Metode Filter Gaussian

Junaidy B Sanger, Immanuela P. Saputro P. Saputro, Yunita Komalig
DOI: https://doi.org/10.33650/jeecom.v5i1.5894



Abstract

Image is a multimedia component rich in information and has an essential role as an information provider. However, the images encountered often experience a decrease in quality, such as defects or noise, causing the information conveyed from these images less clear. Noise causes the image to be too contrasted, blurry, or not sharp enough. One type of noise is contrast noise. Image Smoothing here is one of the operations to improve quality which aims to smooth out images with unbalanced contrast noise. Disturbances in the image are generally in the form of variations in the intensity of a pixel that is not correlated with neighboring pixels. Contrasting images are caused by uneven lighting, which can cause the information in the image to be reduced and difficult to interpret. For this reason, quality improvement must be made to get a better image. In this study, the softening of contrasting images uses the Gaussian Filter method. This filter has the effect of equalizing the gray distance to make the image obtained smoother. Based on the results of the tests, it got an accuracy of 83.3%, meaning that the application's performance is suitable for image smoothing.



Keywords

Image Smoothing, Gaussian Filter, Contrast Image, Application

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References

R. A. Sholihin and B. H. Purwoto, "Jurnal Emitor," Perbaikan Citra dengan Menggunakan Median Filter dan Metode Histogram Equalization, vol. 14, no. 2, p. 40, 2014.

D. Sundani, et al., "Seminar Nasional Teknologi Informasi dan Komunikasi," Aplikasi Pelembutan Citra (Image Smoothing) Berdasarkan Komputasi Klasik dan Kuantum, p. 138, 2014.

A. Wedianto, et al., "Jurnal Media Infotama," Analisa Perbandingan Metode Filter Gaussian, Mean dan Median terhadap Reduksi Noise, vol. 12, p. 23, 2016.

Hasnah, "Jurnal Infotek," Penerapan Metode Sobel dan Gaussian dalam Mendeteksi Tepi dan Memperbaiki Kualitas Citra, vol. 1, p. 48, 2016.

Warsiti, "Majalah Ilmiah Informasi dan Teknologi Ilmiah," Perancangan Aplikasi Pengurangan Noise pada Citra Digital Menggunakan Filter Gaussian, vol. 11, p. 72, 2016.

B. Yuwono, "Telematika," Image Smoothing Menggunakan Mean Filtering, Median Filtering, Modus Filtering dan Gaussian Filtering, vol. 7, p. 65, 2010.

S. Sinurat and E. R. Siagian, “Pelita Informatika: Informasi dan Informatika”, Peningkatan Kualitas Citra Dengan Gaussian Filter Terhadap Citra Hasil Deteksi Robert, vol. 9, p. 225, 2021

R. D. Kusumanto and A. N. Tompunu, "Seminar Nasional Teknologi Informasi & Komunikasi Terapan 2011 (Semantik 2011)," Pengolahan Citra Digital Untuk Mendeteksi Obyek Menggunakan Pengolahan Warna Model Normalisasi RGB, 2011.

W. Gazali, et al., "Jurnal Mat Stat.," penerapan Metode Konvolusi dalam Pengolahan Citra Digital, vol. 12, p. 105, 2012.


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10.33650/jeecom.v5i1.5894


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Creative Commons License
 
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Journal of Electrical Engineering and Computer (JEECOM)
Published by LP3M Nurul Jadid University, Indonesia, Probolinggo, East Java, Indonesia.