Results 71 to 80 of about 557,712 (297)

Blind Deconvolution with Scale Ambiguity

open access: yesApplied Sciences, 2020
Recent years have witnessed significant advances in single image deblurring due to the increasing popularity of electronic imaging equipment. Most existing blind image deblurring algorithms focus on designing distinctive image priors for blur kernel ...
Wanshu Fan   +3 more
doaj   +1 more source

Convolutional Deblurring for Natural Imaging

open access: yes, 2019
In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration.
Hosseini, Mahdi S.   +1 more
core   +1 more source

vEMRec: High‐Resolution Volume Electron Microscopy Reconstruction Based on Structure‐Preserving and High‐Fidelity 3D Alignment

open access: yesAdvanced Science, EarlyView.
vEMRec is a frequency‐adaptive computational framework for three‐dimensional alignment in volume electron microscopy. It integrates feature‐based rigid alignment with Gaussian filter‐guided elastic registration to correct rigid misalignments and nonlinear distortions while preserving structural fidelity.
Zhenbang Zhang   +7 more
wiley   +1 more source

Deep Self-Learning Network for Adaptive Pansharpening

open access: yesRemote Sensing, 2019
Deep learning (DL)-based paradigms have recently made many advances in image pansharpening. However, most of the existing methods directly downscale the multispectral (MSI) and panchromatic (PAN) images with default blur kernel to construct the training ...
Jie Hu, Zhi He, Jiemin Wu
doaj   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao   +11 more
wiley   +1 more source

Combining Motion Compensation with Spatiotemporal Constraint for Video Deblurring

open access: yesSensors, 2018
We propose a video deblurring method by combining motion compensation with spatiotemporal constraint for restoring blurry video caused by camera shake.
Jing Li, Weiguo Gong, Weihong Li
doaj   +1 more source

Learning to Deblur Images with Exemplars

open access: yes, 2018
Human faces are one interesting object class with numerous applications. While significant progress has been made in the generic deblurring problem, existing methods are less effective for blurry face images.
Hu, Zhe   +3 more
core   +1 more source

Single‐Crystal PZT‐Driven Organic Piezo‐Phototronic Adaptive Transistors Toward Advanced Spatiotemporal Visual Computing

open access: yesAdvanced Science, EarlyView.
Here, we propose a single‐crystal PZT‐based piezo‐phototronic organic adaptive memory transistor (OAMT), achieving a record memory window capacity factor (γ) of 0.87 at a low SS of 200 mV/decade via efficient multi‐field control. The device achieves a high recognition accuracy ∼ 90% in neuromorphic simulations, demonstrates robust fault tolerance under
Chenhao Xu   +8 more
wiley   +1 more source

Restoration of Partial Blurred Image Based on Blur Detection and Classification

open access: yesJournal of Electrical and Computer Engineering, 2016
A new restoration algorithm for partial blurred image which is based on blur detection and classification is proposed in this paper. Firstly, a new blur detection algorithm is proposed to detect the blurred regions in the partial blurred image.
Dong Yang, Shiyin Qin
doaj   +1 more source

Edge-based blur kernel estimation using patch priors [PDF]

open access: yesIEEE International Conference on Computational Photography (ICCP), 2013
Blind image deconvolution, i.e., estimating a blur kernel k and a latent image x from an input blurred image y, is a severely ill-posed problem. In this paper we introduce a new patch-based strategy for kernel estimation in blind deconvolution. Our approach estimates a “trusted” subset of x by imposing a patch prior specifically tailored towards ...
null Libin Sun   +3 more
openaire   +1 more source

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