Recent progress in image deblurring
This paper comprehensively reviews the recent development of image deblurring, including
non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques …
non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques …
From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur
Removing pixel-wise heterogeneous motion blur is challenging due to the ill-posed nature
of the problem. The predominant solution is to estimate the blur kernel by adding a prior, but …
of the problem. The predominant solution is to estimate the blur kernel by adding a prior, but …
Learning to deblur
We describe a learning-based approach to blind image deconvolution. It uses a deep
layered architecture, parts of which are borrowed from recent work on neural network …
layered architecture, parts of which are borrowed from recent work on neural network …
Blind deconvolution using a normalized sparsity measure
D Krishnan, T Tay, R Fergus - CVPR 2011, 2011 - ieeexplore.ieee.org
Blind image deconvolution is an ill-posed problem that requires regularization to solve.
However, many common forms of image prior used in this setting have a major drawback in …
However, many common forms of image prior used in this setting have a major drawback in …
Differentiable compound optics and processing pipeline optimization for end-to-end camera design
Most modern commodity imaging systems we use directly for photography—or indirectly rely
on for downstream applications—employ optical systems of multiple lenses that must …
on for downstream applications—employ optical systems of multiple lenses that must …
Single frame atmospheric turbulence mitigation: A benchmark study and a new physics-inspired transformer model
Image restoration algorithms for atmospheric turbulence are known to be much more
challenging to design than traditional ones such as blur or noise because the distortion …
challenging to design than traditional ones such as blur or noise because the distortion …
Non-uniform deblurring for shaken images
Photographs taken in low-light conditions are often blurry as a result of camera shake, ie a
motion of the camera while its shutter is open. Most existing deblurring methods model the …
motion of the camera while its shutter is open. Most existing deblurring methods model the …
[图书][B] Introduction to inverse problems in imaging
Fully updated throughout, with several new chapters, this second edition of Introduction to
Inverse Problems in Imaging guides advanced undergraduate and graduate students in …
Inverse Problems in Imaging guides advanced undergraduate and graduate students in …
Accelerating atmospheric turbulence simulation via learned phase-to-space transform
Fast and accurate simulation of imaging through atmospheric turbulence is essential for
developing turbulence mitigation algorithms. Recognizing the limitations of previous …
developing turbulence mitigation algorithms. Recognizing the limitations of previous …
At-ddpm: Restoring faces degraded by atmospheric turbulence using denoising diffusion probabilistic models
Although many long-range imaging systems are designed to support extended vision
applications, a natural obstacle to their operation is degradation due to atmospheric …
applications, a natural obstacle to their operation is degradation due to atmospheric …