Penerapan Filter Adaptif Untuk Pengurangan Noise Pada Citra Digital

Authors

  • Cindya Putri Hidayat Siregar Universitas Islam Negeri Sumatera Utara
  • Evra Tiara Syahputri Universitas Islam Negeri Sumatera Utara
  • Nurjannah Hasibuan Universitas Islam Negeri Sumatera Utara
  • Yusril Burhani Batubara Universitas Islam Negeri Sumatera Utara
  • Try Widyawanti Universitas Islam Negeri Sumatera Utara
  • Supiyandi Universitas Pembangunan Panca Budi Medan

Keywords:

Adaptive filter, noise reduction, digital image, image processing, Gaussian noise, salt-and-pepper noise, speckle noise, image quality

Abstract

Noise reduction in digital images is one of the main challenges in image processing. Noise can be caused by various factors such as camera sensors, environmental conditions, and data compression. Adaptive filters have become an effective method to reduce noise without sacrificing important details in the image. This study aims to evaluate the performance of different types of adaptive filters, including Adaptive Median Filter, Wiener Filter, and Anisotropic Diffusion Filter, in reducing Gaussian noise, salt-and-pepper noise, and speckle noise. The experimental results show that the Adaptive Median Filter is very effective for reducing salt-and-pepper noise, while the Wiener Filter gives the best results for Gaussian noise and speckle noise. The Anisotropic Diffusion Filter shows balanced performance for all types of noise with satisfactory visual results. Although adaptive filters have higher computational complexity, the gains in image quality make them feasible for applications that require high-quality results. This research confirms the great potential of adaptive filters in improving digital image quality and provides recommendations for practical applications in various fields.

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Published

2024-07-10

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