In the fast-growing field of computer vision, input image quality is critical in determining model prediction accuracy and reliability. However, real-world data is rarely perfect. From blurry surveillance footage to grainy medical scans, low-quality or noisy images are a common challenge that can significantly degrade the performance of vision models.