Results 61 to 70 of about 15,742 (208)
Zero-shot realistic image deblurring with consistency model
At present, diffusion-based image deblurring methods rely on paired blurry-clear datasets for training, and the types of blur causes in image synthesis cannot yet be determined with sufficient precision to model real-world scene blur datasets ...
Zhaohan Wang +2 more
doaj +1 more source
Blur-Robust Object Detection Using Feature-Level Deblurring via Self-Guided Knowledge Distillation
Images captured from real-world environments often include blur artifacts resulting from camera movement, dynamic object motion, or out-of-focus.
Sung-Jin Cho +3 more
doaj +1 more source
A Framework for Fast Image Deconvolution with Incomplete Observations
In image deconvolution problems, the diagonalization of the underlying operators by means of the FFT usually yields very large speedups. When there are incomplete observations (e.g., in the case of unknown boundaries), standard deconvolution techniques ...
Almeida, Luis B. +3 more
core +3 more sources
ABSTRACT Purpose Blood T1 is a key parameter for hemodynamic quantification in both non‐contrast‐ and contrast‐enhanced imaging. Individual vessel T1 has been measured using a modified Look–Locker scheme with multi‐shot EPI or FLASH in high spatial resolution, requiring ∼1 min.
Zechen Xu, Feng Xu, Qin Qin, Dan Zhu
wiley +1 more source
A Generic Framework for Depth Reconstruction Enhancement
We propose a generic depth-refinement scheme based on GeoNet, a recent deep-learning approach for predicting depth and normals from a single color image, and extend it to be applied to any depth reconstruction task such as super resolution, denoising and
Hendrik Sommerhoff, Andreas Kolb
doaj +1 more source
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain
This paper presents a novel strategy for high-fidelity image restoration by characterizing both local smoothness and nonlocal self-similarity of natural images in a unified statistical manner. The main contributions are three-folds.
Gao, Wen +4 more
core +1 more source
A Preconditioned Majorization‐Minimization Method for ℓ2$$ {\ell}^2 $$‐ℓq$$ {\ell}^q $$ Minimization
ABSTRACT The need to minimize a linear combination of an expression that involves an ℓq$$ {\ell}^q $$‐norm of a linear transformation of the computed solution and the ℓ2$$ {\ell}^2 $$‐norm of the residual error arises in image restoration as well as in statistics.
A. Buccini +3 more
wiley +1 more source
Simultaneous Stereo Video Deblurring and Scene Flow Estimation
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
VDTR: Video Deblurring With Transformer
Video deblurring is still an unsolved problem due to the challenging spatio-temporal modeling process. While existing convolutional neural network-based methods show a limited capacity for effective spatial and temporal modeling for video deblurring. This paper presents VDTR, an effective Transformer-based model that makes the first attempt to adapt ...
Mingdeng Cao +4 more
openaire +2 more sources
Deep Learning Integration in Optical Microscopy: Advancements and Applications
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari +5 more
wiley +1 more source

