Results 71 to 80 of about 4,335 (202)
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
Learning to Extract a Video Sequence from a Single Motion-Blurred Image
, 2018 We present a method to extract a video sequence from a single motion-blurred image. Motion-blurred images are the result of an averaging process, where instant frames are accumulated over time during the exposure of the sensor.
Favaro, Paolo +2 more
core +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
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
, 2018 Advances in image restoration and enhancement techniques have led to discussion about how such algorithmscan be applied as a pre-processing step to improve automatic visual recognition. In principle, techniques like deblurring and super-resolution should
Banerjee, Sreya +4 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
Reblur2Deblur: Deblurring Videos via Self-Supervised Learning
, 2018 Motion blur is a fundamental problem in computer vision as it impacts image quality and hinders inference. Traditional deblurring algorithms leverage the physics of the image formation model and use hand-crafted priors: they usually produce results that ...
Chen, Huaijin +5 more
core +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
Simultaneous Stereo Video Deblurring and Scene Flow Estimation
, 2017 Videos for outdoor scene often show unpleasant blur effects due to the large relative motion between the camera and the dynamic objects and large depth variations. Existing works typically focus monocular video deblurring.
Dai, Yuchao +3 more
core +1 more source
FCUnet: An Underwater Image Enhancement Hybrid Network via Fused Feature‐Guided Cross‐Attention
IET Image Processing, Volume 19, Issue 1, January/December 2025.This paper proposes a hybrid CNN‐transformer network for enhancing underwater images. Our approach integrated cross‐attention into the U‐shaped structure with fused feature guidance, designing a colour deviation preprocessing module, a feature fusion unit and a multi‐term loss function to enhance feature extraction capability and adaptability of the ...
Jie Zhu +4 more
wiley +1 more source