Blur Level

Blur level, encompassing both the presence and degree of image blurring, is a crucial factor impacting image quality and the performance of computer vision systems. Current research focuses on developing advanced algorithms, often employing deep learning architectures like convolutional neural networks (CNNs) and transformers, to address blur in various contexts, including image restoration, super-resolution, and object detection. These efforts aim to improve image quality, enhance the robustness of AI models to image degradation, and enable new applications in diverse fields such as medical imaging, autonomous driving, and photography. The development of effective blur mitigation techniques is vital for advancing the reliability and accuracy of numerous image-processing applications.