Local Blur Aware

Local blur aware techniques aim to improve image and video deblurring by specifically addressing blur caused by local motion or variations in focus, rather than solely tackling global blur from camera shake. Current research focuses on developing models that can effectively detect and classify different types of local blur, often employing neural networks with mechanisms like gated architectures or blur-specific loss functions to enhance deblurring performance. These advancements are significant for improving image quality in various applications, including mobile photography, video processing, and medical imaging, where accurate representation of fine details is crucial.