Blurry images usually exhibit similar blur at various locations across the
image domain, a property barely captured in nowadays blind deblurring neural
networks. We show that when extracting patches of similar underlying blur is
possible, jointly processing the stack of patches yields superior accuracy than
handling them separately. Our collaborative scheme is implemented in a neural
architecture with a pooling layer on the stack dimension. We present three
practical patch extraction strategies for image sharpening, camera shake
removal and optical aberration correction, and validate the proposed approach
on both synthetic and real-world benchmarks. For each blur instance, the
proposed collaborative strategy yields significant quantitative and qualitative
improvements.

利用卷积神经网络协同处理不同模糊下的图像补偿，以提高图像清晰度和质量。

协作式盲图像去模糊

Collaborative Blind Image Deblurring

Videos captured with hand-held cameras often suffer from a significant amount
of blur, mainly caused by the inevitable natural tremor of the photographer's
hand. In this work, we present an algorithm that removes blur due to camera
shake by combining information in the Fourier domain from nearby frames in a
video. The dynamic nature of typical videos with the presence of multiple
moving objects and occlusions makes this problem of camera shake removal
extremely challenging, in particular when low complexity is needed. Given an
input video frame, we first create a consistent registered version of
temporally adjacent frames. Then, the set of consistently registered frames is
block-wise fused in the Fourier domain with weights depending on the Fourier
spectrum magnitude. The method is motivated from the physiological fact that
camera shake blur has a random nature and therefore, nearby video frames are
generally blurred differently. Experiments with numerous videos recorded in the
wild, along with extensive comparisons, show that the proposed algorithm
achieves state-of-the-art results while at the same time being much faster than
its competitors.

本文介绍了一种在视频中使用傅里叶域处理、基于加权块的全局优化算法消除相机抖动带来的模糊问题，通过在多个相邻帧内组合信息达到图像稳定。