Exemplar-based image inpainting using adaptive two-stage structure-tensor based priority function and nonlocal filtering

2022 ◽  
pp. 103430
Author(s):  
Ting Xu ◽  
Ting-Zhu Huang ◽  
Liang-Jian Deng ◽  
Xi-Le Zhao ◽  
Jin-Fan Hu
Keyword(s):  
Image Inpainting ◽  
Stage Structure ◽  
Structure Tensor ◽  
Two Stage ◽  
Priority Function

Design of Low Power Track and Hold Circuit Based on Two Stage Structure

2008 ◽  
Vol E91-C (6) ◽  
pp. 894-902
Author(s):  
T. SATO ◽  
I. MATSUMOTO ◽  
S. TAKAGI ◽  
N. FUJII
Keyword(s):  
Low Power ◽  
Stage Structure ◽  
Two Stage

scholarly journals Tunable viscosity modification with diluted particles: when particles decrease the viscosity of complex fluids

2019 ◽  
Vol 297 (11-12) ◽  
pp. 1507-1517 ◽  
Author(s):  
Manuchar Gvaramia ◽  
Gaetano Mangiapia ◽  
Vitaliy Pipich ◽  
Marie-Sousai Appavou ◽  
Sebastian Jaksch ◽  
...  
Keyword(s):  
Complex Fluids ◽  
Stage Structure ◽  
Solid Particles ◽  
Viscosity Reduction ◽  
Spherical Particles ◽  
Steady Increase ◽  
Two Stage ◽  
Apparent Contradiction ◽  
Domain Structures ◽  
Lubrication Effect

Abstract While spherical particles are the most studied viscosity modifiers, they are well known only to increase viscosities, in particular at low concentrations of approx. 1%. Extended studies and theories on non-spherical particles in simple fluids find a more complicated behavior, but still a steady increase with increasing concentration. Involving platelets in combination with complex fluids—in our case, a bicontinuous microemulsion—displays an even more complex scenario that we analyze experimentally and theoretically as a function of platelet diameter using small angle neutron scattering, rheology, and the theory of the lubrication effect, to find the underlying concepts. The clay particles effectively form membranes in the medium that itself may have lamellar aligned domains and surfactant films in the case of the microemulsion. The two-stage structure of clay and surfactant membranes explains the findings using the theory of the lubrication effect. This confirms that layered domain structures serve for lowest viscosities. Starting from these findings and transferring the condition for low viscosities to other complex fluids, namely crude oils, even lowered viscosities with respect to the pure crude oil were observed. This strengthens our belief that also here layered domains are formed as well. This apparent contradiction of a viscosity reduction by solid particles could lead to a wider range of applications where low viscosities are desired. The same concepts of two-stage layered structures also explain the observed conditions for extremely enhanced viscosities at particle concentrations of 1% that may be interesting for the food industry.

A Bayesian two-stage spatially dependent variable selection model for space–time health data

2018 ◽  
Vol 28 (9) ◽  
pp. 2570-2582 ◽  
Author(s):  
Jungsoon Choi ◽  
Andrew B Lawson
Keyword(s):  
Risk Factors ◽  
Variable Selection ◽  
Health Outcomes ◽  
Stage Structure ◽  
Health Data ◽  
Space Time ◽  
Regression Coefficients ◽  
Two Stage ◽  
Epidemiological Modeling ◽  
Confounding Bias

In space–time epidemiological modeling, most studies have considered the overall variations in relative risk to better estimate the effects of risk factors on health outcomes. However, the associations between risk factors and health outcomes may vary across space and time. Especially, the temporal patterns of the covariate effects may depend on space. Thus, we propose a Bayesian two-stage spatially dependent variable selection approach for space–time health data to determine the spatially varying subsets of regression coefficients with common temporal dependence. The two-stage structure allows reduction of the spatial confounding bias in the estimates of the regression coefficients. A simulation study is conducted to examine the performance of the proposed two-stage model. We apply the proposed model to the number of inpatients with lung cancer in 159 counties of Georgia, USA.

An impulsive two-stage predator–prey model with stage-structure and square root functional responses

2016 ◽  
Vol 119 ◽  
pp. 91-107 ◽  
Author(s):  
Xiangmin Ma ◽  
Yuanfu Shao ◽  
Zhen Wang ◽  
Mengzhuo Luo ◽  
Xianjia Fang ◽  
...  
Keyword(s):  
Stage Structure ◽  
Square Root ◽  
Functional Responses ◽  
Two Stage ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Prey Model

scholarly journals Improved Exemplar based Image Inpainting using Structure Tensor

2014 ◽  
Vol 96 (15) ◽  
pp. 9-14 ◽  
Author(s):  
Ankur G.Patel ◽  
Shashwat Kumar ◽  
Ankit D. Prajapati
Keyword(s):  
Image Inpainting ◽  
Structure Tensor

scholarly journals Quality Improvement for Exemplar-based Image Inpainting using a Modified Searching Mechanism

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Mariwan Wahid Ahmed ◽  
Alan Anwer Abdulla
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Euclidean Distance ◽  
Image Inpainting ◽  
Input Image ◽  
Second Step ◽  
Research Areas ◽  
Potential Applications ◽  
Priority Function ◽  
Popular Images

Digital image processing has a significant impact in different research areas including medical image processing, biometrics, image inpainting, object detection, information hiding, and image compression. Image inpainting is a science of reconstructing damaged parts of digital images and filling-in regions in which information are missing which has many potential applications such as repairing scratched images, removing unwanted objects, filling missing area, and repairing old images. In this paper, an image inpainting algorithm is developed based on exemplar, which is one of the most important and popular images inpainting technique, to fill-in missing area that caused either by removing unwanted objects, by image compression, by scratching image, or by image transformation through internet. In general, image inpainting consists of two main steps: The first one is the priority function. In this step, the algorithm decides to select which patch has the highest priority to be filled at the first. The second step is the searching mechanism to find the most similar patch to the selected highest priority patch to be inpainted. This paper concerns the second step and an improved searching mechanism is proposed to select the most similar patch. The proposed approach entails three steps: (1) Euclidean distance is used to find the similarity between the highest priority patches which need to be inpainted with each patch of the input image, (2) the position/location distance between those two patches is calculated, and (3) the resulted value from the first step is summed with the resulted value obtained from the second step. These steps are repeated until the last patch from the input image is checked. Finally, the smallest distance value obtained in step 3 is selected as the most similar patch. Experimental results demonstrated that the proposed approach gained a higher quality in terms of both objectives and subjective compared to other existing algorithms.

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