Results 51 to 60 of about 547 (178)
Single Image Defocus Deblurring Based on Structural Information Enhancement
IEEE AccessDefocus deblurring is an important task in computer vision that aims to bring images back to clarity. Over recent years, both blind defocuse deblurring and non-blind defocuse deblurring methods have made great progress in the single image defocus ...
Guangming Feng +3 more
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Progressive deep network for blind motion image deblurring
Xi'an Gongcheng Daxue xuebao, 2023 The multi-stage deep neural network in the blind motion image deblurring task lacks a large range of receptive fields and it was difficult to reasonably interact with the image features of each stage.
WANG Xiaohua +4 more
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Enhancing convolutional neural network generalizability via low‐rank weight approximation
IET Image Processing, Volume 20, Issue 1, January/December 2026.A self‐supervised framework is proposed for image denoising based on the Tucker low‐rank tensor approximation. With the proposed design, we are able to characterize our denoiser with fewer parameters and train it based on a single image, which considerably improves the model's generalizability and reduces the cost of data acquisition. Abstract Noise is
Chenyin Gao, Shu Yang, Anru R. Zhang
wiley +1 more source
Semi-blind image deblurring based on framelet prior
Signal, Image and Video Processing, 2023 The problem of image blurring is one of the most studied topics in the field of image processing. Image blurring is caused by various factors such as hand or camera shake. To restore the blurred image, it is necessary to know information about the point spread function (PSF).
Mohammad Zarebnia, Reza Parvaz
openaire +4 more sources
Diffusion Models and Its Applications in Image Dehazing: A Survey
IET Image Processing, Volume 20, Issue 1, January/December 2026.1.This survey represents the first systematic and comprehensive overview of diffusion model‐based image dehazing, aiming to provide a valuable guide for future researchers and stimulate continued progress in this field. 2.We summarize relevant papers along with their corresponding code links and other resources for image dehazing and all‐in‐one image ...
Liangyu Zhu +6 more
wiley +1 more source
Enhanced Illumination for Robust Steel Wire Rope Damage Detection Using IRetinexformer and LIME
IET Image Processing, Volume 20, Issue 1, January/December 2026.This study proposes a novel surface damage detection method for mine hoisting steel wire ropes (HSWRs) that integrates an improved Retinexformer with BM3D denoising and the LIME algorithm to address challenges of uneven illumination and shadow occlusion in low‐light conditions.
Fengzhong Sun +5 more
wiley +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
IET Image Processing, Volume 20, Issue 1, January/December 2026.To address the limitations of existing defocus deblurring methods—such as the inability of single discriminators to balance local texture and global colour consistency, and insufficient capture of long‐range dependencies by traditional generators—this paper proposes DAD‐GAN, an end‐to‐end generative adversarial network integrating a parallel dual ...
Yuemeng Liu, Dongjie Chen, Zhihui Yang
wiley +1 more source
SAR‐Flow: Spatially Adaptive Rectified Flow for Efficient Low‐Light Image Enhancement
IET Image Processing, Volume 20, Issue 1, January/December 2026.SAR‐Flow overcomes the limitations of traditional flow‐based models in low‐light image enhancement by replacing the standard isotropic Gaussian assumption with a spatially adaptive noise field tailored to the image's local signal‐to‐noise ratio. Additionally, it leverages rectified flow to straighten complex probability transport paths into highly ...
Xuecheng Liao +4 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