Results 81 to 90 of about 293,019 (211)
Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network
, 2023 In this paper, we address the problem of blind deblurring with high efficiency. We propose a set of lightweight deep-wiener-network to finish the task with real-time speed.
Yu, Yang, Li, Runjia, Haywood, Charlie
core
Sensors, 2020 Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the ...
Quan Zhou, Mingyue Ding, Xuming Zhang
doaj +1 more source
Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging
Advanced Functional Materials, Volume 35, Issue 23, June 5, 2025.A thermally stable organic memristor based on a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented, demonstrating reliable, gradual resistance switching across a wide temperature range (153–573 K).
Ziyu Lv +15 more
wiley +1 more source
Laser &Photonics Reviews, Volume 19, Issue 12, June 18, 2025.This review explores deconvolution techniques in optical coherence tomography (OCT), addressing resolution degradation from point‐spread functions (PSF). It reviews foundational principles (e.g., Richardson‐Lucy deconvolution) to advanced AI‐driven methods, emphasizing clinical translation and interdisciplinary collaboration. Real‐world implementations
Syeda Aimen Abbasi +6 more
wiley +1 more source
Fast Weighted Total Variation Regularization Algorithm for Blur Identification and Image Restoration
IEEE Access, 2016 Images obtained from unconstrained environments may be blurred by unknown kernels and affected due to noise. This paper presents a new total variation minimization-based method for blindly deblurring such images. Unlike the alternating optimization-based
Haiying Liu +3 more
doaj +1 more source
Dual-Channel Contrast Prior for Blind Image Deblurring
IEEE Access, 2020 In this article, a dual-channel contrast prior (Dual-CP) is proposed for blind image deblurring. The prior is motivated by the observation that image contrast will significantly degenerate after the blurring process, which is proved in both ...
Dayi Yang, Xiaojun Wu
doaj +1 more source
Improved conditional diffusion model for image super‐resolution
IET Image Processing, Volume 19, Issue 1, January/December 2025.Our article introduces a diffusion model based on Mean‐Reverting Stochastic Differential Equations (SDE), leveraging ENAFBlocks to enhance noise prediction performance compared to traditional ResBlocks. The Mean‐Reverting SDE utilizes low‐resolution images as means to mitigate diffusion model randomness, while an LR Encoder captures hidden information ...
Rui Wang, Ningning Zhou
wiley +1 more source
Deformable Attention Network for Efficient Space‐Time Video Super‐Resolution
IET Image Processing, Volume 19, Issue 1, January/December 2025.Recent space‐time video super‐resolution (STVSR) works combine temporal interpolation and spatial super‐resolution in a unified framework, they face challenges in computational complexity across both temporal and spatial dimensions, particularly in achieving accurate intermediate frame interpolation and efficient temporal information utilisation.
Hua Wang +3 more
wiley +1 more source
PSF-constraints based iterative blind deconvolution method for image deblurring
, 2009 In recent years, Image Deblurring techniques have played an essential role in the field of Image Processing. In image deblurring, there are several kinds of blurred image such as motion blur, defocused blur and gaussian blur. Many methods to address this
Mo, Xuan +5 more
core +1 more source
Multi‐Scale Frequency Enhancement Network for Blind Image Deblurring
IET Image Processing, Volume 19, Issue 1, January/December 2025.We propose a multi‐scale frequency enhancement network (MFENet) for blind image deblurring, which integrates multi‐scale feature extraction and frequency enhancement to recover fine details. MFENet includes a multi‐scale feature extraction module (MS‐FE) and a frequency enhanced blur perception module (FEBP) to improve performance on deblurring ...
YaWen Xiang +5 more
wiley +1 more source