Results 71 to 80 of about 4,574 (198)
Understanding Kernel Size in Blind Deconvolution
, 2019 Most blind deconvolution methods usually pre-define a large kernel size to guarantee the support domain. Blur kernel estimation error is likely to be introduced, yielding severe artifacts in deblurring results.
Ren, Dongwei, Si-Yao, Li, Yin, Qian
core +1 more source
Blind Motion Deblurring through SinGAN Architecture
CoRR, 2020 Blind motion deblurring involves reconstructing a sharp image from an observation that is blurry. It is a problem that is ill-posed and lies in the categories of image restoration problems. The training data-based methods for image deblurring mostly involve training models that take a lot of time.
Harshil Jain +3 more
openaire +2 more sources
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
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
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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
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
, 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
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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
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
A Neural Approach to Blind Motion Deblurring [PDF]
, 2016 We present a new method for blind motion deblurring that uses a neural network trained to compute estimates of sharp image patches from observations that are blurred by an unknown motion kernel. Instead of regressing directly to patch intensities, this network learns to predict the complex Fourier coefficients of a deconvolution filter to be applied to
openaire +2 more sources