Results 41 to 50 of about 9,413,043 (217)

Blind Image Deblurring via Local Maximum Difference Prior

open access: yesIEEE Access, 2020
Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required.
Jing Liu   +4 more
doaj   +1 more source

Collaborative Blind Image Deblurring

open access: yes2024 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   +4 more sources

NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images [PDF]

open access: yes, 2022
In recent years, deep neural network-based restoration methods have achieved state-of-the-art results in various image deblurring tasks. However, one major drawback of deep learning-based deblurring networks is that large amounts of blurry-clean image ...
Nair, Nithin Gopalakrishnan   +2 more
core  

Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image

open access: yesTikrit 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

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

open access: yesInternational Endodontic Journal, EarlyView.
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi   +6 more
wiley   +1 more source

An Efficient Blind Image Deblurring Algorithm

open access: yes, 2010
This paper presents a novel algorithm which concerns with the fast implement of blind image deblurring with a well-reconstructed original image. Firstly, we model both the original image and the blur utilizing the harmonic model in the Sobolev image ...
Su Xiao   +3 more
core   +1 more source

SID: Sensor-Assisted Image Deblurring System for Mobile Devices

open access: yesIEEE 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

Adaptive blind image deblurring and denoising

open access: yesScandinavian 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

Fixing a blurred photograph: blind image deblurring

open access: yes, 2023
This project presents a deep learning-based approach to blind image deblurring using a convolutional neural network. The trained model can produce a deblurred output using only the blurred image as input and exhibits improved image quality, as ...
Teo, Hong Wei
core  

Multi‐Scale Transformer for Image Restoration

open access: yesCAAI 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

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