Fast compressed sensing analysis for imaging reconstruction with primal dual interior point algorithm

Chao, Lianying; Han, Jiefei; Yan, Lijun; Sun, Liying; Huang, Fan; Zhu, Zhengbo; Wei, Shili; Ji, Huiru; Ma, Donglin

doi:10.1016/j.optlaseng.2020.106082

Cited by 10 publications

(5 citation statements)

References 27 publications

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“…According to the prime dual method, the solution can be achieved by narrowing the dual gap between the feasible solution of the prime and dual problem. It starts from an arbitrary chosen initial point and searching and going to the direction to find the optimal solution by applying the classical Newton method [39]. Implementation of this approach is computationally possible as free software packages are already available to solve the problem iteratively.…”

Section: Prime-dual Interior-point Methodsmentioning

confidence: 99%

Compressed sensing based fingerprint imaging system using a chaotic model-based deterministic sensing matrix

Hailemariam

Gupta

2022

Multimed Tools Appl

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A novel deterministic sensing matrix design approach applied to enable secured compressed sensing and transmission of fingerprint images. The performance of the sensing matrix was analyzed in detail by varying compressed sensing and security parameters. The number of sampling and sparse coefficient are the parameters taken under consideration from compressed sensing, whereas the encryption key is from the security scheme. The first stage in the performance study is acquiring the signal, and followed by sparsely modelling it using Orthogonal Matching Pursuit (OMP) algorithm. The sparse modelled data is multiplied by the proposed deterministic partial orthogonal Discrete Cosine Transform (DCT) sensing matrix to reduce its dimension and encrypt it. To introduce confusion on the DCT matrix rows, the pseudorandom permutation is applied to the DCT matrix rows before sensing matrix derivation. Additionally, recovering and decryption of the compressed image accomplished with the help of a convex optimization method. The results obtained from the simulation of the proposed system confirmed that a better Peak Signal to Noise Ratio (PSNR) than the recommended value for wireless transmission is archived using a sample below 25% without losing a significant number of fingerprint minutiae.

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Section: Prime-dual Interior-point Methodsmentioning

confidence: 99%

Compressed sensing based fingerprint imaging system using a chaotic model-based deterministic sensing matrix

Hailemariam

Gupta

2022

Multimed Tools Appl

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“…( 9) According to the prime dual method, the solution can be achieved by narrowing the dual gap between the feasible solution of the prime and dual problem. It starts from an arbitrary chosen initial point and searching direction then it going to find the optimal solution by applying the classical Newton method [37]. Implementation of this approach computationally possible as a free software package available to solve the problem iteratively.…”

Section: Prime-dual Interior-point Methodsmentioning

confidence: 99%

Compressed Sensing System for a Fingerprint Image Recognition Using Sensing Matrix with Chaotic Model-Based Deterministic Row Indexes

Hailemariam

Gupta

2021

Preprint

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This paper proposes a novel design approach for a secured compressed sensing system for fingerprint imaging and its transmission. In the proposed design, the first stage is acquiring the signal followed by sparsely modeling it using Orthogonal Matching Pursuit (OMP) algorithm. In addition to compressing, to guaranty its security, we multiply the sparse modeled data by a novel deterministic partially orthogonal Discrete Cosine Transform (DCT) sensing matrix. Furthermore, the construction of the sensing matrix uses a modified Multiplicative Linear Congruential Generator (MLCG) to select the row index appropriately from chaotically re-arranged rows of DCT pseudo-randomly. On the other hand, the simultaneous recovering and decryption of the compressed image accomplished with the help of a convex optimization method. The proposed system tested by employing different image and security assessment techniques. The results show that we have archived better Peak Signal to Noise Ratio (PSNR) than the recommended value for wireless transmission using samples below 25%.

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“…In essence, it is an algorithm that combines logarithmic barrier function, Lagrange function method, and Newton iteration method for optimization calculation by introducing relaxation variable and Lagrange multiplier vector and has the advantages of these three methods at the same time. The primal dual 5 Wireless Communications and Mobile Computing interior point method starts from the feasible initial interior point and searches for optimization within the feasible region along the steepest descent direction of the primal dual path until it approaches the optimal solution [26]. When solving large-scale linear programming problems, it has been proved theoretically that it has polynomial time complexity and second-order convergence characteristics.…”

Section: Design Of the Trust Region Interior Point Algorithm For Nonl...mentioning

confidence: 99%

New Solutions of Nonlinear Equations Constrained by Bounded Variables under Edge Computation

Wang

2022

Wireless Communications and Mobile Computing

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Aiming at the problem of low global convergence and local convergence rate of trust region interior points of bounded variable constrained nonlinear equations, a trust region interior point algorithm for bounded variable constrained nonlinear equations under edge calculation is designed. By constructing the basic function form of nonlinear equations constrained by bounded variables, the boundary of nonlinear equations is determined by Gauss Newton iterative process to ensure the global convergence of changes; solve the original objective function, analyze the trust region subproblem of the unconstrained optimization problem, and generate an acceptable region. The region is generated through two-dimensional example interpretation. The interior points in the acceptable region are determined by the primal dual interior point method, and the interior points in the acceptable region are optimized. With the help of edge calculation, the trust region interior point programming model of bounded variable constrained nonlinear equations is designed to realize the algorithm design. The experimental results show that the designed algorithm can improve the trust region interior point global convergence and local convergence rate of nonlinear equations with bounded variable constraints.

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Fast compressed sensing analysis for imaging reconstruction with primal dual interior point algorithm

Cited by 10 publications

References 27 publications

Compressed sensing based fingerprint imaging system using a chaotic model-based deterministic sensing matrix

Compressed sensing based fingerprint imaging system using a chaotic model-based deterministic sensing matrix

Compressed Sensing System for a Fingerprint Image Recognition Using Sensing Matrix with Chaotic Model-Based Deterministic Row Indexes

New Solutions of Nonlinear Equations Constrained by Bounded Variables under Edge Computation

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