Results 71 to 80 of about 4,369 (201)
Dual-Channel Contrast Prior for Blind Image Deblurring
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
Total Fractional-Order Variation-Based Constraint Image Deblurring Problem
When deblurring an image, ensuring that the restored intensities are strictly non-negative is crucial. However, current numerical techniques often fail to consistently produce favorable results, leading to negative intensities that contribute to ...
Shahid Saleem +2 more
doaj +1 more source
Learning to Extract a Video Sequence from a Single Motion-Blurred Image
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
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
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss . DeblurGAN achieves state-of-the art performance both in the structural similarity measure and visual appearance ...
Budzan, Volodymyr +4 more
core +1 more source
Improved conditional diffusion model for image super‐resolution
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
Fast Weighted Total Variation Regularization Algorithm for Blur Identification and Image Restoration
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
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
Deformable Attention Network for Efficient Space‐Time Video Super‐Resolution
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
Multi‐Scale Frequency Enhancement Network for Blind Image Deblurring
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

