scholarly journals Morphological and Linear Scale Spaces for Fiber Enhancement in DW-MRI

2012 ◽  
Vol 46 (3) ◽  
pp. 326-368 ◽  
Author(s):  
Remco Duits ◽  
Tom Dela Haije ◽  
Eric Creusen ◽  
Arpan Ghosh
Keyword(s):  
Linear Scale ◽  
Scale Spaces

scholarly journals Erratum to: Morphological and Linear Scale Spaces for Fiber Enhancement in DW-MRI

2013 ◽  
Vol 46 (3) ◽  
pp. 369-369 ◽  
Author(s):  
Remco Duits ◽  
Tom Dela Haije ◽  
Eric Creusen ◽  
Arpan Ghosh
Keyword(s):  
Linear Scale ◽  
Scale Spaces

Adding a visual linear scale probability to the pioped probability of pulmonary embolism

1997 ◽  
Vol 38 (3) ◽  
pp. 458-463
Author(s):  
F. Christiansen ◽  
T. Nilsson ◽  
K. Måre ◽  
A. Carlsson
Keyword(s):  
Pulmonary Embolism ◽  
Linear Scale ◽  
Scale Probability

scholarly journals A Lightweight Fusion Distillation Network for Image Deblurring and Deraining

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5312
Author(s):  
Yanni Zhang ◽  
Yiming Liu ◽  
Qiang Li ◽  
Jianzhong Wang ◽  
Miao Qi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Deblurring ◽  
Image Features ◽  
Image Feature ◽  
Model Complexity ◽  
Small Scale ◽  
Feature Maps ◽  
Learning Framework ◽  
Channel Information ◽  
Scale Spaces

Recently, deep learning-based image deblurring and deraining have been well developed. However, most of these methods fail to distill the useful features. What is more, exploiting the detailed image features in a deep learning framework always requires a mass of parameters, which inevitably makes the network suffer from a high computational burden. We propose a lightweight fusion distillation network (LFDN) for image deblurring and deraining to solve the above problems. The proposed LFDN is designed as an encoder–decoder architecture. In the encoding stage, the image feature is reduced to various small-scale spaces for multi-scale information extraction and fusion without much information loss. Then, a feature distillation normalization block is designed at the beginning of the decoding stage, which enables the network to distill and screen valuable channel information of feature maps continuously. Besides, an information fusion strategy between distillation modules and feature channels is also carried out by the attention mechanism. By fusing different information in the proposed approach, our network can achieve state-of-the-art image deblurring and deraining results with a smaller number of parameters and outperform the existing methods in model complexity.

scholarly journals Infrared and visible image fusion via octave Gaussian pyramid framework

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Yan ◽  
Qun Hao ◽  
Jie Cao ◽  
Rizvi Saad ◽  
Kun Li ◽  
...  
Keyword(s):  
Image Fusion ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Visible Image ◽  
Composite Image ◽  
Multiscale Decomposition ◽  
Gaussian Pyramid ◽  
Fusion Methods ◽  
Scale Spaces ◽  
Fusion Framework

AbstractImage fusion integrates information from multiple images (of the same scene) to generate a (more informative) composite image suitable for human and computer vision perception. The method based on multiscale decomposition is one of the commonly fusion methods. In this study, a new fusion framework based on the octave Gaussian pyramid principle is proposed. In comparison with conventional multiscale decomposition, the proposed octave Gaussian pyramid framework retrieves more information by decomposing an image into two scale spaces (octave and interval spaces). Different from traditional multiscale decomposition with one set of detail and base layers, the proposed method decomposes an image into multiple sets of detail and base layers, and it efficiently retains high- and low-frequency information from the original image. The qualitative and quantitative comparison with five existing methods (on publicly available image databases) demonstrate that the proposed method has better visual effects and scores the highest in objective evaluation.

scholarly journals Boundary Morphology for Hierarchical Simplification of Archaeological Fragments

2020 ◽  
Vol 4 (1) ◽  
pp. 46-63
Author(s):  
Hanan ElNaghy ◽  
Leo Dorst
Keyword(s):  
Mathematical Morphology ◽  
Masking Effect ◽  
Morphological Operations ◽  
Fracture Surfaces ◽  
Morphological Approach ◽  
Archaeological Artifacts ◽  
Scale Spaces ◽  
Extrusion Method

AbstractWhen fitting archaeological artifacts, one would like to have a representation that simplifies fragments while preserving their complementarity. In this paper, we propose to employ the scale-spaces of mathematical morphology to hierarchically simplify potentially fitting fracture surfaces. We study the masking effect when morphological operations are applied to selected subsets of objects. Since fitting locally depends on the complementarity of fractures only, we introduce ‘Boundary Morphology’ on surfaces rather than volumes. Moreover, demonstrating the Lipschitz nature of the terracotta fractures informs our novel extrusion method to compute both closing and opening operations simultaneously. We also show that in this proposed representation the effects of abrasion and uncertainty are naturally bounded, justifying the morphological approach. This work is an extension of our contribution earlier published in the proceedings of ISMM2019 [10].

Increasing Treatment Lifetime through Sustained Release of Scale Inhibitor from Scale Inhibitor Nanoparticles

SPE Journal ◽  
2021 ◽  
pp. 1-7
Author(s):  
Huili Guan ◽  
Austin Lim ◽  
Joshua Hernandez ◽  
Jenn-Tai Liang
Keyword(s):  
Sustained Release ◽  
Functional Group ◽  
Proof Of Concept ◽  
Linear Scale ◽  
Scale Inhibitor ◽  
Concept Study ◽  
Inhibition Concentration ◽  
Calcium And Magnesium ◽  
Inhibitor Treatment ◽  
Over Time

Summary Scale can cause flow assurance issues because of damage to the near-wellbore region and in production facilities. Scale inhibitors are often used to help mitigate these problems. The main focus of this proof-of-concept study is to examine the ability of a newly developed crosslinked nanosized scale inhibitor (NSI) particle to inhibit scale formation through sustained release of scale inhibitor into a model brine and increase scale inhibitor treatment lifetime. Results from minimum inhibition concentration (MIC) measurements showed that, at 95°C, the MIC decreased gradually from 10 ppm at day 0 to 5 ppm after 9 days and eventually reached a very low MIC of 2 ppm after 49 days. These findings are consistent with our hypothesis that the sustained release of linear scale inhibitor from the NSI would result in a decrease in MIC over time caused by an increased amount of linear scale inhibitor being released into the model brine. Also, attaching 2-acrylamido-2-methyl-1-propanesulfonic functional group (AMPS) to NSI successfully inhibits the pseudoscale formation when the scale inhibitor comes into contact with the calcium and magnesium in the model brine. Results from sandpack floods showed that NSI increased the treatment lifetime from 3 pore volumes (PV) postflush throughput, for the traditional scale inhibitor, to 35 to 105 PV postflush throughput. These results support our hypothesis that sustained release of the trapped NSI nanoparticles can improve the treatment lifetime.

Sparsification Scale-Spaces

2019 ◽  
pp. 303-314
Author(s):  
Marcelo Cárdenas ◽  
Pascal Peter ◽  
Joachim Weickert
Keyword(s):  
Scale Spaces

Inverse Scale Spaces for Nonlinear Regularization

2006 ◽  
Vol 27 (1) ◽  
pp. 41-50 ◽  
Author(s):  
Johan Lie ◽  
Jan M. Nordbotten
Keyword(s):  
Nonlinear Regularization ◽  
Scale Spaces
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