An Efficient Image Preprocessing Technique for Land Use Analysis by Using Remote Sensing Images

2021 ◽  
Vol 10 (1) ◽  
pp. 316-320
Keyword(s):  
Singular Values ◽  
Ease Of Use ◽  
Basic Knowledge ◽  
New Technique ◽  
Computationally Efficient ◽  
Singular Value Decomposition Method ◽  
Block Based ◽  
Use Of Social Media ◽  
Preprocessing Technique ◽  
Value Decomposition

With the widespread availability of image manipulating software and with ease of use, anyone with basic knowledge can modify the image without leaving any traces in the image. People believe in whatever they see in an image, but it is not necessary that the content has to be real. With the wide use of social media people with malicious intent share images that are modified and make you believe that they are real and by doing so they can influence people’s opinion which is a grave danger for society.In copy paste attack a part of the image is copied and pasted on to a different region of the same image, this pasted region can be detected by using the block-based method, but when the copied region is rotated orthogonally or if it is flipped before pasting on to the destination, such pasted regions are impossible to detect with the block-based approach.In this paper we are proposing a new technique to detect rotated or flipped pasted regions in an image and the performance of this new technique is compared with the SVD (Singular Value Decomposition) method used for the same purpose. The proposed new technique overcomes the rounding off errors in singular values of SVD method and computationally efficient than SVD and also computes the angle of rotation

scholarly journals A Through-the-Wall Imaging Approach Based on a TSVD/Variable-Exponent Lebesgue-Space Method

2021 ◽  
Vol 13 (11) ◽  
pp. 2028
Author(s):  
Andrea Randazzo ◽  
Cristina Ponti ◽  
Alessandro Fedeli ◽  
Claudio Estatico ◽  
Paolo D’Atanasio ◽  
...  
Keyword(s):  
Variable Exponent ◽  
Scattering Problem ◽  
Inverse Scattering Problem ◽  
Source Spectrum ◽  
Computationally Efficient ◽  
Geometrical Properties ◽  
Singular Value Decomposition Method ◽  
The Time Domain ◽  
Value Decomposition ◽  
Wall Imaging

A hybrid inversion scheme for through-the-wall imaging is proposed in this paper. The approach is based on a linearized model of the inverse-scattering problem, employing the Green’s function developed for a layered background. The reconstruction is obtained by means of a Landweber-like iterative method performing a regularization in the framework of variable-exponent Lebesgue spaces. Thanks to the non-conventional geometrical properties of such spaces, it is possible to enhance the reconstruction capabilities, e.g., by promoting sparseness and reducing over-smoothing. The exponent function defining the specific space adopted in the inversion procedure is adaptively obtained directly from the measured data, through a truncated-singular value decomposition method. In this way, it is possible to precompute and reuse in both steps, for a given scenario, all the matrices necessary in the inversion process, thus leading to a computationally efficient solving strategy. The effectiveness of the approach is evaluated by using experimental data obtained with a commercial GPR apparatus employing a pulsed source field. A fast Fourier transform is applied to the time-domain measurements to extract frequency-domain data at a set of frequencies in the source spectrum, which are fed in input to the imaging scheme. Very good reconstruction capabilities are obtained both with a single metallic target, as well as in a challenging two targets layout including both a metallic object and a low-permittivity target.

A SVD and Modified Firefly Optimization Based Robust Digital Image Watermarking Technique

2017 ◽  
Vol 7 (7) ◽  
pp. 268
Author(s):  
Chauhan Usha ◽  
Singh Rajeev Kumar
Keyword(s):  
Digital Media ◽  
Firefly Algorithm ◽  
Image Watermarking ◽  
Singular Values ◽  
Robust Watermarking ◽  
Scaling Factors ◽  
Geometric Attacks ◽  
Host Image ◽  
Firefly Optimization ◽  
Value Decomposition

Digital Watermarking is a technology, to facilitate the authentication, copyright protection and Security of digital media. The objective of developing a robust watermarking technique is to incorporate the maximum possible robustness without compromising with the transparency. Singular Value Decomposition (SVD) using Firefly Algorithm provides this objective of an optimal robust watermarking technique. Multiple scaling factors are used to embed the watermark image into the host by multiplying these scaling factors with the Singular Values (SV) of the host image. Firefly Algorithm is used to optimize the modified host image to achieve the highest possible robustness and transparency. This approach can significantly increase the quality of watermarked image and provide more robustness to the embedded watermark against various attacks such as noise, geometric attacks, filtering attacks etc.

scholarly journals Distributed Singular Value Decomposition Method for Fast Data Processing in Recommendation Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2284
Author(s):  
Krzysztof Przystupa ◽  
Mykola Beshley ◽  
Olena Hordiichuk-Bublivska ◽  
Marian Kyryk ◽  
Halyna Beshley ◽  
...  
Keyword(s):  
Distributed Systems ◽  
Singular Value Decomposition ◽  
Data Processing ◽  
Message Passing ◽  
Message Passing Interface ◽  
Recommendation Systems ◽  
Singular Value ◽  
Singular Value Decomposition Method ◽  
Value Decomposition ◽  
Svd Method

The problem of analyzing a big amount of user data to determine their preferences and, based on these data, to provide recommendations on new products is important. Depending on the correctness and timeliness of the recommendations, significant profits or losses can be obtained. The task of analyzing data on users of services of companies is carried out in special recommendation systems. However, with a large number of users, the data for processing become very big, which causes complexity in the work of recommendation systems. For efficient data analysis in commercial systems, the Singular Value Decomposition (SVD) method can perform intelligent analysis of information. With a large amount of processed information we proposed to use distributed systems. This approach allows reducing time of data processing and recommendations to users. For the experimental study, we implemented the distributed SVD method using Message Passing Interface, Hadoop and Spark technologies and obtained the results of reducing the time of data processing when using distributed systems compared to non-distributed ones.

scholarly journals BlocklyXR: An Interactive Extended Reality Toolkit for Digital Storytelling

2021 ◽  
Vol 11 (3) ◽  
pp. 1073
Author(s):  
Kwanghee Jung ◽  
Vinh T. Nguyen ◽  
Jaehoon Lee
Keyword(s):  
Technology Acceptance ◽  
Digital Storytelling ◽  
Visual Programming ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Programming Approach ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Positive Effects ◽  
Block Based

Traditional in-app virtual reality (VR)/augmented reality (AR) applications pose a challenge of reaching users due to their dependency on operating systems (Android, iOS). Besides, it is difficult for general users to create their own VR/AR applications and foster their creative ideas without advanced programming skills. This paper addresses these issues by proposing an interactive extended reality toolkit, named BlocklyXR. The objective of this research is to provide general users with a visual programming environment to build an extended reality application for digital storytelling. The contextual design was generated from real-world map data retrieved from Mapbox GL. ThreeJS was used for setting up, rendering 3D environments, and controlling animations. A block-based programming approach was adapted to let users design their own story. The capability of BlocklyXR was illustrated with a use case where users were able to replicate the existing PalmitoAR utilizing the block-based authoring toolkit with fewer efforts in programming. The technology acceptance model was used to evaluate the adoption and use of the interactive extended reality toolkit. The findings showed that visual design and task technology fit had significantly positive effects on user motivation factors (perceived ease of use and perceived usefulness). In turn, perceived usefulness had statistically significant and positive effects on intention to use, while there was no significant impact of perceived ease of use on intention to use. Study implications and future research directions are discussed.

Aggregation Method of Multi-Criteria Evaluations in New and Renewable Energy Power Plants: A Case Study

2009 ◽  
Author(s):  
Jiang-Jiang Wang ◽  
Chun-Fa Zhang ◽  
You-Yin Jing
Keyword(s):  
Renewable Energy ◽  
Nuclear Power ◽  
Power Plants ◽  
Economic Cost ◽  
Evaluation Result ◽  
Singular Value Decomposition Method ◽  
Multi Criteria Evaluation ◽  
Potential Development ◽  
Value Decomposition ◽  
Grey Relational

The multi-criteria evaluation methods of complex systems such as the new and renewable technologies gradually spring up. The feasibility of energy power plants is evaluated and considered from many aspects, such as technology, economic cost and environment protection. However, the energy power plants’ ranking results in different methods or different weighs can be different. Accordingly, the sequencing results should be aggregated and analyzed, and then an integrated result should be given out. Aiming to get the specific evaluation result, 10 kinds of energy power plants, such as hydro, nuclear, wind, geothermal and biomass plants are considered and evaluated. The singular value decomposition method is employed to aggregate the evaluation results in grey relational method, PROMENTHEE II method, and other results from literature. The integrated evaluation result shows that the hydro and nuclear power plants are located on the first place and the renewable energy power plants have great potential development in the future.

Dynamic contraction and fatigue analysis in biceps brachii muscles using synchrosqueezed wavelet transform and singular value features

2021 ◽  
pp. 095441192110480
Author(s):  
Lakshmi M Hari ◽  
Gopinath Venugopal ◽  
Swaminathan Ramakrishnan
Keyword(s):  
Wavelet Transform ◽  
Biceps Brachii ◽  
Singular Value ◽  
Time Frequency ◽  
Singular Value Decomposition Method ◽  
Dynamic Contractions ◽  
Synchrosqueezed Wavelet Transform ◽  
Value Decomposition ◽  
Neuromuscular Conditions ◽  
Semg Signals

In this study, the dynamic contractions and the associated fatigue condition in biceps brachii muscle are analysed using Synchrosqueezed Wavelet Transform (SST) and singular value features of surface Electromyography (sEMG) signals. For this, the recorded signals are decomposed into time-frequency matrix using SST. Two analytic functions namely Morlet and Bump wavelets are utilised for the analysis. Singular Value Decomposition method is applied to this time-frequency matrix to derive the features such as Maximum Singular Value (MSV), Singular Value Entropy (SVEn) and Singular Value Energy (SVEr). The results show that both these wavelets are able to characterise nonstationary variations in sEMG signals during dynamic fatiguing contractions. Increase in values of MSV and SVEr with the progression of fatigue denotes the presence of nonstationarity in the sEMG signals. The lower values of SVEn with the progression of fatigue indicate the randomness in the signal. Thus, it appears that the proposed approach could be used to characterise dynamic muscle contractions under varied neuromuscular conditions.

scholarly journals A modified truncation singular value decomposition method for solving ill-posed problems

2018 ◽  
Vol 13 ◽  
pp. 174830181881360 ◽  
Author(s):  
Zhenyu Zhao ◽  
Riguang Lin ◽  
Zehong Meng ◽  
Guoqiang He ◽  
Lei You ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Decomposition Method ◽  
Singular Value ◽  
Numerical Results ◽  
New Method ◽  
Truncated Singular Value Decomposition ◽  
Singular Value Decomposition Method ◽  
Ill Posed ◽  
Value Decomposition

A modified truncated singular value decomposition method for solving ill-posed problems is presented in this paper, in which the solution has a slightly different form. Both theoretical and numerical results show that the limitations of the classical TSVD method have been overcome by the new method and very few additive computations are needed.

Sign in / Sign up

Export Citation Format

Share Document