Results 61 to 70 of about 15,547 (189)

Blur-Robust Object Detection Using Feature-Level Deblurring via Self-Guided Knowledge Distillation

IEEE Access, 2022
Images captured from real-world environments often include blur artifacts resulting from camera movement, dynamic object motion, or out-of-focus.
Sung-Jin Cho, Seung-Wook Kim, Seung-Won Jung, Sung-Jea Ko   +3 more
doaj   +1 more source

Light Field Blind Motion Deblurring

, 2017
We study the problem of deblurring light fields of general 3D scenes captured under 3D camera motion and present both theoretical and practical contributions.
Ng, Ren, Ramamoorthi, Ravi, Srinivasan, Pratul P.   +2 more
core   +1 more source

Progressive Colour Equalisation and Detail Refinement for Underwater Image Enhancement

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Underwater image enhancement remains a critical challenge in computational vision due to complex distortions caused by wavelength‐dependent light absorption and scattering. This paper introduces CEDFNet, a novel two‐stage framework that leverages advanced computational intelligence techniques for robust and high‐fidelity underwater image ...
Songbai Liu, Jiacheng Huang
wiley   +1 more source

Survey on Image Deblurring Algorithms [PDF]

Jisuanji kexue
Image deblurring is a classic problem in computer vision,aiming to recover sharp visual information from blurry input images or videos.Blur is often caused by factors such as camera misfocus,camera shake,or fast-moving objects.Traditional deblurring ...
CHEN Kang, LIN Jianhan, LIU Yuanjie
doaj   +1 more source

A Generic Framework for Depth Reconstruction Enhancement

Journal of Imaging, 2022
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

Faster gradient descent and the efficient recovery of images

, 2013
Much recent attention has been devoted to gradient descent algorithms where the steepest descent step size is replaced by a similar one from a previous iteration or gets updated only once every second step, thus forming a {\em faster gradient descent ...
Ascher, Uri, Huang, Hui
core   +1 more source

Fibre phantom generation using FibreSimulator: an open‐source Python tool

Journal of Synchrotron Radiation, EarlyView.
FibreSimulator is an open‐source tool for generating realistic 3D phantoms of unidirectional fibre‐reinforced polymers, enabling customizable fibre structures and simulating computed tomography scanning for algorithm development and validation.Fibre‐reinforced polymer composites are utilized across many industries for their stiffness and strength ...
Mary Chris Roperos Go, Daniël M. Pelt, Anirudh Kohli, Philip J. Withers, K. Joost Batenburg   +4 more
wiley   +1 more source

Image Restoration Using Joint Statistical Modeling in Space-Transform Domain

, 2014
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, Ma, Siwei, Xiong, Ruiqin, Zhang, Jian, Zhao, Debin   +4 more
core   +1 more source

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
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, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 more
wiley   +1 more source

VDTR: Video Deblurring With Transformer

IEEE Transactions on Circuits and Systems for Video Technology, 2023
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, Yanbo Fan, Yong Zhang, Jue Wang, Yujiu Yang   +4 more
openaire   +2 more sources