<![CDATA[In today's digital era, digital images play an important role in various fields, including image processing, surveillance systems, and medical image processing. However, one of the main challenges is that low-resolution images often experience quality degradation, so the loss of important details caused by noise and blurring makes the information in the image unclear. To overcome this problem, various image processing methods have been developed, including the Otsu Thresholding and Canny Edge Detection methods. This study will compare two methods for improving the quality of low-resolution images, namely Otsu Thresholding and Canny Edge Detection. This experiment was conducted to determine how effective the two methods are by testing several low-resolution image samples and then evaluating the results based on the PSNR, MSE, and SSIM metric values. The experimental results obtained show that the Otsu Thresholding method outperforms Canny Edge Detection in terms of improving image quality, as evidenced by better PSNR, lower MSE, and SSIM closer to 1. Thus, Otsu Thresholding is recommended as a more effective and optimal method in low-resolution image processing. Therefore, it is hoped that the results of this study can be a reference for developing more effective and optimal low-resolution image processing methods in the future.]]>
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