<![CDATA[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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