Results 61 to 70 of about 13,900 (206)
Fast and easy blind deblurring using an inverse filter and PROBE
PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively.
J Kotera +11 more
core +1 more source
Sparse Poisson Noisy Image Deblurring
Deblurring noisy Poisson images has recently been a subject of an increasing amount of works in many areas such as astronomy and biological imaging. In this paper, we focus on confocal microscopy, which is a very popular technique for 3-D imaging of biological living specimens that gives images with a very good resolution (several hundreds of ...
Carlavan, Mikael, Blanc-Féraud, Laure
openaire +4 more sources
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi +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
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
Motion Deblurring in Image Color Enhancement by WGAN
Motion deblurring and image enhancement are active research areas over the years. Although the CNN-based model has an advanced state of the art in motion deblurring and image enhancement, it fails to produce multitask results when challenged with the ...
Jiangfan Feng, Shuang Qi
doaj +1 more source
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
Adversarial Spatio-Temporal Learning for Video Deblurring
Camera shake or target movement often leads to undesired blur effects in videos captured by a hand-held camera. Despite significant efforts having been devoted to video-deblur research, two major challenges remain: 1) how to model the spatio-temporal ...
Li, Hongdong +5 more
core +1 more source
This article presents an image deblurring method using ℓ0-norm-based deblurring and ℓ2-norm-based texture-aware image fusion for remote sensing images.
Heunseung Lim +4 more
doaj +1 more source
ABSTRACT Purpose To achieve high resolution (≤ 1 mm isotropic) whole‐brain perfusion imaging at 7 T with next generation ASL pulse sequence, reconstruction algorithm, and MRI hardware. Methods We capitalized on three major innovations: (1) FLASH‐based pseudo‐Continuous ASL (pCASL) sequence with rotated golden‐angle stack‐of‐spirals (rGA‐SoS) sampling; (
Chenyang Zhao +8 more
wiley +1 more source

