Photon-Limited Deblurring using Algorithm Unrolling
Image deblurring in a photon-limited condition is ubiquitous in a variety of low-light applications such as photography, microscopy and astronomy. However, presence of photon shot noise due to low-illumination and/or short exposure time makes the deblurring task substantially more challenging . This paper presents an algorithm unrolling approach for the photon-limited deblurring problem that unrolls a Plug-and-Play algorithm using a fixed-iteration network. By modifying the typical two-variable splitting to a three-variable splitting, our unrolled network is differentiable and can be trained end-to-end. We demonstrate the usage of our algorithm on real photon-limited image data.
Code (0)
등록된 구현이 없습니다.
Tasks
AstronomyDeblurringImage DeblurringRolling Shutter CorrectionSimilar Papers 제목 키워드 기반
Photon Limited Non-Blind Deblurring Using Algorithm Unrolling
Image deblurring in photon-limited conditions is ubiquitous in a variety of low-light applications such as photography, microscopy, and astronomy. However, the presence of photon shot noise due to low illumination and/or…
AstronomyDeblurringImage DeblurringRolling Shutter CorrectionBayesian Based Unrolling for Reconstruction and Super-resolution of Single-Photon Lidar Systems
Deploying 3D single-photon Lidar imaging in real world applications faces several challenges due to imaging in high noise environments and with sensors having limited resolution. This paper presents a deep learning algor…
Super-ResolutionDeep Algorithm Unrolling for Blind Image Deblurring
Blind image deblurring remains a topic of enduring interest. Learning based approaches, especially those that employ neural networks have emerged to complement traditional model based methods and in many cases achieve va…
Blind Image DeblurringDeblurringImage DeblurringRolling Shutter CorrectionDeep, convergent, unrolled half-quadratic splitting for image deconvolution
In recent years, algorithm unrolling has emerged as a powerful technique for designing interpretable neural networks based on iterative algorithms. Imaging inverse problems have particularly benefited from unrolling-base…
DeblurringImage DeblurringImage DeconvolutionGraph Attention-Driven Bayesian Deep Unrolling for Dual-Peak Single-Photon Lidar Imaging
Single-photon Lidar imaging offers a significant advantage in 3D imaging due to its high resolution and long-range capabilities, however it is challenging to apply in noisy environments with multiple targets per pixel. T…
Graph Attention