Defocus Blur

Defocus blur, the blurring of images due to a limited depth of field, is a significant challenge in various imaging applications, hindering accurate scene reconstruction and object recognition. Current research focuses on developing robust methods to mitigate or even leverage defocus blur, employing techniques like neural radiance fields (NeRFs), Gaussian splatting, and various deep learning architectures to either remove blur from existing images or synthesize realistic defocus effects. These advancements are crucial for improving the quality of 3D reconstructions from real-world images, enhancing microscopic imaging for medical diagnosis, and enabling novel view synthesis with realistic depth-of-field effects in computer graphics.