Results 71 to 80 of about 547 (178)
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
More Realistic Edges, Textures, and Colors for Image Non‐Homogeneous Dehazing
IET Image Processing, Volume 19, Issue 1, January/December 2025.The study proposes an image dehazing method to improve performance in non‐homogeneous and/or dense haze scenarios, ensuring high texture detail and color fidelity in dehazed images.The proposed method employs a multi‐scale encoder–decoder structure to effectively capture finer edge and texture details.
Hairu Guo +4 more
wiley +1 more source
Image Deblurring Method with Fractional-order Total Variation and Adaptive Regularization Parameters
工程科学与技术, 2018 In order to better recovery texture details of images, avoid the difficulty of selecting the regularization parameters when solving the image deblurring model, a novel non-blind image deblurring method by using fractional order TV (FOTV) and adaptive ...
Xiaomei YANG +3 more
doaj
Blind Deblurring via a Novel Recursive Deep CNN Improved by Wavelet Transform
IEEE Access, 2018 Blind image deconvolution is an ill-posed problem, which is mainly addressed by the regularization methods. Wavelet transform is an effective denoising method related to regularized inversion. In this paper, wavelet transform is utilized to decompose and
Chao Min +3 more
doaj +1 more source
Patch-Wise Blind Image Deblurring Via Michelson Channel Prior
IEEE Access, 2019 Motion blur exists in many computer vision tasks, including faces, texts, and low-illumination images etc. It has been proved that Dark Channel Prior (DCP) and Bright Channel Prior (BCP) can both help the image deblurring by enhancing the dark or bright ...
Guoquan Wen +4 more
doaj +1 more source
FPGA-Based Real-Time Deblurring and Enhancement for UAV-Captured Infrared Imagery
Remote SensingIn response to the inherent limitations of uncooled infrared imaging devices and the image degradation caused by UAV (Unmanned Aerial Vehicle) platform motion, resulting in low contrast and blurred details, a novel single-image blind deblurring and ...
Jianghua Cheng +4 more
doaj +1 more source
Image Blind Deblurring Using an Adaptive Patch Prior
Tsinghua Science and Technology, 2019 Image blind deblurring uses an estimated blur kernel to obtain an optimal restored original image with sharp features from a degraded image with blur and noise artifacts.
Yongde Guo, Hongbing Ma
doaj +1 more source
A Variational Neural Network Based on Algorithm Unfolding for Image Blind Deblurring
Applied SciencesImage blind deblurring is an ill-posed inverse problem in image processing. While deep learning approaches have demonstrated effectiveness, they often lack interpretability and require extensive data.
Shaoqing Gong +5 more
doaj +1 more source
Blind Image Deblurring via Bayesian Estimation Using Expected Loss
IEEE AccessThis paper introduces a new approach to single image blind deblurring via Bayesian estimation using expected loss, diverging from traditional maximum a posteriori (MAP) estimation methods that are limited by the delta kernel problem-a phenomenon where ...
Jinook Lee, Moon Gi Kang
doaj +1 more source
A Fast Nonlinear Sparse Model for Blind Image Deblurring. [PDF]
J ImagingZhang Z +8 more
europepmc +1 more source