Compression of Steganographed PPG Signal With Guaranteed Reconstruction Quality Based on Optimum Truncation of Singular Values and ASCII Character Encoding

2019 ◽  
Vol 66 (7) ◽  
pp. 2081-2090 ◽  
Author(s):  
Sourav Kumar Mukhopadhyay ◽  
M. Omair Ahmad ◽  
M.N.S. Swamy
Keyword(s):  
Singular Values ◽  
Ascii Character ◽  
Reconstruction Quality

Single Image Dehazing by Predicting Atmospheric Scattering Parameters

2020 ◽  
Vol 2020 (1) ◽  
pp. 74-77
Author(s):  
Simone Bianco ◽  
Luigi Celona ◽  
Flavio Piccoli
Keyword(s):  
Reference Image ◽  
Single Image ◽  
Scattering Parameters ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Local Structures ◽  
Full Reference ◽  
Reconstruction Quality ◽  
Single Image Dehazing

In this work we propose a method for single image dehazing that exploits a physical model to recover the haze-free image by estimating the atmospheric scattering parameters. Cycle consistency is used to further improve the reconstruction quality of local structures and objects in the scene as well. Experimental results on four real and synthetic hazy image datasets show the effectiveness of the proposed method in terms of two commonly used full-reference image quality metrics.

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.

Estimation of the Number of Signal Components Based on Singular Values of Noise Subspace

2011 ◽  
Vol 33 (9) ◽  
pp. 2039-2044 ◽  
Author(s):  
Xin-peng Zhou ◽  
Feng Han ◽  
Guo-hua Wei ◽  
Si-liang Wu
Keyword(s):  
Singular Values ◽  
Noise Subspace

Analysis of multiplicity of Hankel singular values of control systems

2015 ◽  
Vol 76 (2) ◽  
pp. 205-218 ◽  
Author(s):  
L. A. Mironovskii ◽  
T. N. Solov’eva
Keyword(s):  
Control Systems ◽  
Singular Values ◽  
Hankel Singular Values

scholarly journals Ramanujan’s function k(τ)=r(τ)r 2(2τ) and its modularity

2020 ◽  
Vol 18 (1) ◽  
pp. 1727-1741
Author(s):  
Yoonjin Lee ◽  
Yoon Kyung Park
Keyword(s):  
Continued Fraction ◽  
Quadratic Field ◽  
Singular Values ◽  
Modular Function ◽  
Imaginary Quadratic Field ◽  
Modular Equations ◽  
Positive Rational Number ◽  
Congruence Relations ◽  
Symmetry Relations ◽  
Ray Class Field

Abstract We study the modularity of Ramanujan’s function k ( τ ) = r ( τ ) r 2 ( 2 τ ) k(\tau )=r(\tau ){r}^{2}(2\tau ) , where r ( τ ) r(\tau ) is the Rogers-Ramanujan continued fraction. We first find the modular equation of k ( τ ) k(\tau ) of “an” level, and we obtain some symmetry relations and some congruence relations which are satisfied by the modular equations; these relations are quite useful for reduction of the computation cost for finding the modular equations. We also show that for some τ \tau in an imaginary quadratic field, the value k ( τ ) k(\tau ) generates the ray class field over an imaginary quadratic field modulo 10; this is because the function k is a generator of the field of the modular function on Γ 1 ( 10 ) {{\mathrm{\Gamma}}}_{1}(10) . Furthermore, we suggest a rather optimal way of evaluating the singular values of k ( τ ) k(\tau ) using the modular equations in the following two ways: one is that if j ( τ ) j(\tau ) is the elliptic modular function, then one can explicitly evaluate the value k ( τ ) k(\tau ) , and the other is that once the value k ( τ ) k(\tau ) is given, we can obtain the value k ( r τ ) k(r\tau ) for any positive rational number r immediately.

scholarly journals New diagonal micropolarizer arrays designed by an improved model in fourier domain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jia Hao ◽  
Yan Wang ◽  
Kui Zhou ◽  
Xiaochang Yu ◽  
Yiting Yu
Keyword(s):  
Stokes Parameters ◽  
Fourier Domain ◽  
Extended Model ◽  
Reconstruction Accuracy ◽  
Polarization Imaging ◽  
New Class ◽  
Reconstruction Quality ◽  
Improved Design ◽  
Improved Model

AbstractThe design of micropolarizer array (MPA) patterns in Fourier domain provides an efficient approach to reconstruct and investigate the polarization information. Inspired by Alenin’s works, in this paper, we propose an improved design model to cover both 2 × N MPAs and other original MPAs, by which an entirely new class of MPA patterns is suggested. The performance of the new patterns is evaluated through Fourier domain analysis and numerical simulations compared with the existing MPAs. Particularly, we analyze the reconstruction accuracy of the first three Stokes parameters and degree of linear polarization (DoLP) in detail. The experimental results confirm that the 2 × 2 × 2 MPA provides the highest reconstruction quality of s0, s1, s2 and DoLP in terms of quantitative measures and visual quality, while the 3 × 3 diagonal MPA achieves the state-of-the-art best results in case of single-snapshot systems. The guidance of this extended model and new diagonal MPAs show its massive potential for the division of focal plane (DoFP) polarization imaging applications.

scholarly journals Microwave thermometry with potential application in non-invasive monitoring of hyperthermia

2020 ◽  
Vol 28 (5) ◽  
pp. 739-750
Author(s):  
Morteza Ghaderi Aram ◽  
Larisa Beilina ◽  
Hana Dobsicek Trefna
Keyword(s):  
Least Squares Method ◽  
Regularization Parameter ◽  
Region Of Interest ◽  
Optimal Choice ◽  
Adaptive Finite Element Method ◽  
Adaptive Finite Element ◽  
Non Invasive ◽  
Full Wave ◽  
Reconstruction Quality ◽  
Regularization Techniques

AbstractIntegration of an adaptive finite element method (AFEM) with a conventional least squares method has been presented. As a 3D full-wave forward solver, CST Microwave Studio has been used to model and extract both electric field distribution in the region of interest (ROI) and S-parameters of a circular array consisting of 16 monopole antennas. The data has then been fed into a differential inversion scheme to get a qualitative indicator of how the temperature distribution evolves over a course of the cooling process of a heated object. Different regularization techniques within the Tikhonov framework are also discussed, and a balancing principle for optimal choice of the regularization parameter was used to improve the image reconstruction quality of every 2D slice of the final image. Targets are successfully imaged via proposed numerical methods.

Stable Calibrations of Six-DOF Serial Robots by Using Identification Models with Equalized Singular Values

Robotica ◽  
2021 ◽  
pp. 1-22
Author(s):  
Zhouxiang Jiang ◽  
Min Huang
Keyword(s):  
Industrial Robot ◽  
Singular Values ◽  
Calibration Method ◽  
Identification Accuracy ◽  
Condition Numbers ◽  
Measurement Instruments ◽  
Unknown Parameters ◽  
Calibration Methods ◽  
Six Dof ◽  
The Stability

SUMMARY In typical calibration methods (kinematic or non-kinematic) for serial industrial robot, though measurement instruments with high resolutions are adopted, measurement configurations are optimized, and redundant parameters are eliminated from identification model, calibration accuracy is still limited under measurement noise. This might be because huge gaps still exist among the singular values of typical identification Jacobians, thereby causing the identification models ill conditioned. This paper addresses such problem by using new identification models established in two steps. First, the typical models are divided into the submodels with truncated singular values. In this way, the unknown parameters corresponding to the abnormal singular values are removed, thereby reducing the condition numbers of the new submodels. However, these models might still be ill conditioned. Therefore, the second step is to further centralize the singular values of each submodel by using a matrix balance method. Afterward, all submodels are well conditioned and obtain much higher observability indices compared with those of typical models. Simulation results indicate that significant improvements in the stability of identification results and the identifiability of unknown parameters are acquired by using the new identification submodels. Experimental results indicate that the proposed calibration method increases the identification accuracy without incurring additional hardware setup costs to the typical calibration method.

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