Implementasi Metode Alpha-Trimmed Mean Filter dan Adaptive Median Filter Untuk Mereduksi Noise Poisson Pada Citra Digital
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Restima Restima
*
Universitas Budi Darma, Medan,
Indonesia
(*) Corresponding Author
Abstract
Basically, every image taking can cause noise in the resulting image. Nooise Poisson, Uniform, Salt and Pepper, Speckle noise are noise models that are common in images. Digital images that have noise can cause problems in the form of images that cannot be interpreted properly by humans. However, noise can be reduced through image enhancement, namely filtering. Filter methods that can be used to reduce noise include AlphaTrimmed Mean Filter and Adaptive Median Filter. The results of this study indicate that the Adaptive Median Filter (AMF) is good for reducing Noise Poisson compared to Alpha-Trimmed Mean Filter (ATMF). The design can later improve the quality of digital images and make it easier for radiologists to analyze images exposed to noise and produce even better image
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References
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Pages: 527-535
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