Results 41 to 50 of about 4,335 (202)
Blind Image Deblurring Based on Local Edges Selection
Applied Sciences, 2019 The edges of images are less sparse when images become blurred. Selecting effective image edges is a vital step in image deblurring, which can help us to build image deblurring models more accurately.
Yue Han, Jiangming Kan
doaj +1 more source
Fast and easy blind deblurring using an inverse filter and PROBE
, 2017 PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively.
J Kotera +11 more
core +1 more source
Collaborative Blind Image Deblurring
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)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.
Eboli, Thomas +2 more
openaire +2 more sources
Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
doaj +1 more source
SID: Sensor-Assisted Image Deblurring System for Mobile Devices
IEEE Access, 2019 Handheld mobile photography is often affected by motion blur due to the difficulty of keeping the camera's stable. The existing processing method is usually a high-cost deblurring process of a computer, which seriously affects the user experience, and ...
Qing Wang +4 more
doaj +1 more source
Recent Progress in Image Deblurring [PDF]
, 2014 This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques.
Tao, Dacheng, Wang, Ruxin
core
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
, 2018 We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss . DeblurGAN achieves state-of-the art performance both in the structural similarity measure and visual appearance ...
Budzan, Volodymyr +4 more
core +1 more source
Adaptive blind image deblurring and denoising
Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 413-441, March 2026.Abstract Blind image deblurring aims to reconstruct the original image from its blurred version without knowing the blurring mechanism. This is a challenging ill‐posed problem because there are infinitely many possible solutions. The ill‐posedness is further exacerbated if the blurring mechanism depends on the pixel location.
Yicheng Kang +2 more
wiley +1 more source
Learning Blind Motion Deblurring
, 2017 As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot frequently yields a blurry result due to unwanted camera shake during recording ...
Hirsch, Michael +3 more
core +1 more source
Multi‐Scale Transformer for Image Restoration
CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 41-54, February 2026.ABSTRACT Although Transformer‐based image restoration methods have demonstrated impressive performance, existing Transformers still insufficiently exploit multiscale information. Previous non‐Transformer‐based studies have shown that incorporating multiscale features is crucial for improving restoration results.
Wuzhen Shi +6 more
wiley +1 more source