scholarly journals A new hybrid $ l_p $-$ l_2 $ model for sparse solutions with applications to image processing

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Xuerui Gao ◽  
Yanqin Bai ◽  
Shu-Cherng Fang ◽  
Jian Luo ◽  
Qian Li
Keyword(s):  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Image Recovery ◽  
Computational Time ◽  
Signal To Noise ◽  
Fixed Point Algorithm ◽  
Proposed Model ◽  
Real World Applications ◽  
Partial Linear ◽  
Sparse Solutions

<p style='text-indent:20px;'>Finding sparse solutions to a linear system has many real-world applications. In this paper, we study a new hybrid of the <inline-formula><tex-math id="M3">\begin{document}$ l_p $\end{document}</tex-math></inline-formula> quasi-norm (<inline-formula><tex-math id="M4">\begin{document}$ 0 &lt;p&lt; 1 $\end{document}</tex-math></inline-formula>) and <inline-formula><tex-math id="M5">\begin{document}$ l_2 $\end{document}</tex-math></inline-formula> norm to approximate the <inline-formula><tex-math id="M6">\begin{document}$ l_0 $\end{document}</tex-math></inline-formula> norm and propose a new model for sparse optimization. The optimality conditions of the proposed model are carefully analyzed for constructing a partial linear approximation fixed-point algorithm. A convergence proof of the algorithm is provided. Computational experiments on image recovery and deblurring problems clearly confirm the superiority of the proposed model over several state-of-the-art models in terms of the signal-to-noise ratio and computational time.</p>

scholarly journals Combined First- and Second-Order Variational Model for Image Compressive Sensing

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Can Feng ◽  
Liang Xiao ◽  
Zhihui Wei
Keyword(s):  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Second Order ◽  
Variational Model ◽  
Mr Images ◽  
Signal To Noise ◽  
Proposed Model ◽  
Numerical Performance ◽  
Minimization Scheme

A hybrid variational model combined first- and second-order total variation for image reconstruction from its finite number of noisy compressive samples is proposed in this paper. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by successively minimizing a sequence of quadratic surrogate penalties. Both the nature and magnetic resonance (MR) images are used to compare its numerical performance with four state-of-the-art algorithms. Experimental results demonstrate that the proposed algorithm obtained a significant improvement over related state-of-the-art algorithms in terms of the reconstruction relative error (RE) and peak signal to noise ratio (PSNR).

scholarly journals Discovery of allenyl acetylene, H2CCCHCCH, in TMC-1

2021 ◽  
Vol 647 ◽  
pp. L3 ◽  
Author(s):  
J. Cernicharo ◽  
C. Cabezas ◽  
M. Agúndez ◽  
B. Tercero ◽  
N. Marcelino ◽  
...  
Keyword(s):  
Column Density ◽  
State Of The Art ◽  
Rotational Temperature ◽  
Signal To Noise Ratio ◽  
Laboratory Data ◽  
The Other ◽  
Signal To Noise ◽  
Chemical Models ◽  
Upper Limit

We present the discovery in TMC-1 of allenyl acetylene, H2CCCHCCH, through the observation of nineteen lines with a signal-to-noise ratio ∼4–15. For this species, we derived a rotational temperature of 7 ± 1 K and a column density of 1.2 ± 0.2 × 1013 cm−2. The other well known isomer of this molecule, methyl diacetylene (CH3C4H), has also been observed and we derived a similar rotational temperature, Tr = 7.0 ± 0.3 K, and a column density for its two states (A and E) of 6.5 ± 0.3 × 1012 cm−2. Hence, allenyl acetylene and methyl diacetylene have a similar abundance. Remarkably, their abundances are close to that of vinyl acetylene (CH2CHCCH). We also searched for the other isomer of C5H4, HCCCH2CCH (1.4-Pentadiyne), but only a 3σ upper limit of 2.5 × 1012 cm−2 to the column density can be established. These results have been compared to state-of-the-art chemical models for TMC-1, indicating the important role of these hydrocarbons in its chemistry. The rotational parameters of allenyl acetylene have been improved by fitting the existing laboratory data together with the frequencies of the transitions observed in TMC-1.

Approximate Full Adders for Energy Efficient Image Processing Applications

2021 ◽  
pp. 2150235
Author(s):  
M. C. Parameshwara
Keyword(s):  
Energy Efficient ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Full Adder ◽  
Signal To Noise ◽  
Design Metrics ◽  
Standard Cell Library ◽  
Cell Library ◽  
Fair Comparison ◽  
Power Delay Product

This paper proposes six novel approximate 1-bit full adders (AFAs) for inexact computing. The six novel AFAs namely AFA1, AFA2, AFA3, AFA4, AFA5, and AFA6 are derived from state-of-the-art exact 1-bit full adder (EFA) architectures. The performance of these AFAs is compared with reported AFAs (RAAs) in terms of design metrics (DMs) and peak-signal-to-noise-ratio (PSNR). The DMs under consideration are power, delay, power-delay-product (PDP), energy-delay-product (EDP), and area. For a fair comparison, the EFAs and proposed AFAs along with RAAs are described in Verilog, simulated, and synthesized using Cadences’ RC tool, using generic 180 nm standard cell library. The unconstrained synthesis results show that: among all the proposed AFAs, the AFA1 and AFA2 are found to be energy-efficient adders with high PSNR. The AFA1 has a total [Formula: see text][Formula: see text][Formula: see text]W, [Formula: see text][Formula: see text]ps, [Formula: see text][Formula: see text]fJ, [Formula: see text][Formula: see text]Js, [Formula: see text][Formula: see text][Formula: see text]m2, and [Formula: see text][Formula: see text]dB. And the AFA2 has the total [Formula: see text][Formula: see text][Formula: see text]W, [Formula: see text][Formula: see text]ps, [Formula: see text][Formula: see text]fJ, [Formula: see text][Formula: see text]Js, [Formula: see text][Formula: see text][Formula: see text]m2, and [Formula: see text][Formula: see text]dB.

scholarly journals An Adaptive Image Inpainting Method Based on Continued Fractions Interpolation

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Lei He ◽  
Yan Xing ◽  
Kangxiong Xia ◽  
Jieqing Tan
Keyword(s):  
Continued Fractions ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Subjective Evaluation ◽  
Image Inpainting ◽  
Rational Interpolation ◽  
Objective Evaluation ◽  
Experimental Results ◽  
Signal To Noise

In view of the drawback of most image inpainting algorithms by which texture was not prominent, an adaptive inpainting algorithm based on continued fractions was proposed in this paper. In order to restore every damaged point, the information of known pixel points around the damaged point was used to interpolate the intensity of the damaged point. The proposed method included two steps; firstly, Thiele’s rational interpolation combined with the mask image was used to interpolate adaptively the intensities of damaged points to get an initial repaired image, and then Newton-Thiele’s rational interpolation was used to refine the initial repaired image to get a final result. In order to show the superiority of the proposed algorithm, plenty of experiments were tested on damaged images. Subjective evaluation and objective evaluation were used to evaluate the quality of repaired images, and the objective evaluation was comparison of Peak Signal to Noise Ratios (PSNRs). The experimental results showed that the proposed algorithm had better visual effect and higher Peak Signal to Noise Ratio compared with the state-of-the-art methods.

scholarly journals Automated Multimodal image fusion for brain tumor detection

2021 ◽  
Vol 3 (1) ◽  
pp. 68-82
Author(s):  
Harpreet Kaur ◽  
◽  
Deepika Koundal ◽  
Virendar Kadyan ◽  
Navneet Kaur ◽  
...  
Keyword(s):  
Image Fusion ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Visual Image ◽  
Fusion Rule ◽  
Resonance Imaging ◽  
Signal To Noise ◽  
Multiple Images ◽  
Fused Image ◽  
Magnetic Resonance Imaging Mri

In medical domain, various multimodalities such as Computer tomography (CT) and Magnetic resonance imaging (MRI) are integrated into a resultant fused image. Image fusion (IF) is a method by which vital information can be preserved by extracting all important information from the multiple images into the resultant fused image. The analytical and visual image quality can be enhanced by the integration of different images. In this paper, a new algorithm has been proposed on the basis of guided filter with new fusion rule for the fusion of different imaging modalities such as MRI and Fluorodeoxyglucose images of brain for the detection of tumor. The performance of the proposed method has been evaluated and compared with state-of-the-art image fusion techniques using various qualitative as well as quantitative evaluation metrics. From the results, it has been observed that more information has achieved on edges and content visibility is also high as compared to the other techniques which makes it more suitable for real applications. The experimental results are evaluated on the basis of with-reference and without-references metric such as standard deviation, entropy, peak signal to noise ratio, mutual information etc.

scholarly journals Blind audio source separation based on a new system model and the Savitzky-Golay filter

2021 ◽  
Vol 72 (3) ◽  
pp. 208-212
Author(s):  
Pengfei Xu ◽  
Yinjie Jia ◽  
Mingxin Jiang
Keyword(s):  
Simple Structure ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
System Model ◽  
High Signal ◽  
Audio Signals ◽  
Signal To Noise ◽  
Proposed Model ◽  
Source Signals ◽  
New System

Abstract Blind source separation (BSS) is a research hotspot in the field of signal processing. This scheme is widely applied to separate a group of source signals from a given set of observations or mixed signals. In the present study, the Savitzky-Golay filter is applied to smooth the mixed signals, adopt a simplified cost function based on the signal to noise ratio (SNR) and obtain the demixing matrix accordingly. To this end, the generalized eigenvalue problem is solved without conventional iterative methods. It is founded that the proposed algorithm has a simple structure and can be easily implemented in diverse problems. The obtained results demonstrate the good performance of the proposed model for separating audio signals in cases with high signal to noise ratios.

scholarly journals A simple model of speech communication and its application to intelligibility enhancement

2021 ◽  
Author(s):  
Willem Kleijn ◽  
RC Hendriks
Keyword(s):  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Speech Communication ◽  
Noisy Environment ◽  
Human Communication ◽  
Signal To Noise ◽  
Message Interpretation ◽  
Message Production ◽  
Personal Use ◽  
Interpretation Process

We introduce a model of communication that includes noise inherent in the message production process as well as noise inherent in the message interpretation process. The production and interpretation noise processes have a fixed signal-to-noise ratio. The resulting system is a simple but effective model of human communication. The model naturally leads to a method to enhance the intelligibility of speech rendered in a noisy environment. State-of-the-art experimental results confirm the practical value of the model. © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

scholarly journals Super resolution DOA estimation based on deep neural network

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wanli Liu
Keyword(s):  
Neural Network ◽  
Potential Application ◽  
Deep Neural Network ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Doa Estimation ◽  
Angular Distance ◽  
Signal To Noise ◽  
Simulation Results

AbstractRecently, deep neural network (DNN) studies on direction-of-arrival (DOA) estimations have attracted more and more attention. This new method gives an alternative way to deal with DOA problem and has successfully shown its potential application. However, these works are often restricted to previously known signal number, same signal-to-noise ratio (SNR) or large intersignal angular distance, which will hinder their generalization in real application. In this paper, we present a novel DNN framework that realizes higher resolution and better generalization to random signal number and SNR. Simulation results outperform that of previous works and reach the state of the art.

scholarly journals A simple model of speech communication and its application to intelligibility enhancement

2021 ◽  
Author(s):  
Willem Kleijn ◽  
RC Hendriks
Keyword(s):  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Speech Communication ◽  
Noisy Environment ◽  
Human Communication ◽  
Signal To Noise ◽  
Message Interpretation ◽  
Message Production ◽  
Personal Use ◽  
Interpretation Process

We introduce a model of communication that includes noise inherent in the message production process as well as noise inherent in the message interpretation process. The production and interpretation noise processes have a fixed signal-to-noise ratio. The resulting system is a simple but effective model of human communication. The model naturally leads to a method to enhance the intelligibility of speech rendered in a noisy environment. State-of-the-art experimental results confirm the practical value of the model. © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

scholarly journals Decimative Spectral Estimation with Unconstrained Model Order

2012 ◽  
Vol 2012 ◽  
pp. 1-10
Author(s):  
Stavroula-Evita Fotinea ◽  
Ioannis Dologlou ◽  
Stylianos Bakamidis ◽  
Theologos Athanaselis
Keyword(s):  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Spectral Estimation ◽  
Hankel Matrix ◽  
State Space Method ◽  
Signal To Noise ◽  
Model Order ◽  
Unconstrained Model ◽  
Nmr Signals ◽  
Space Method

This paper presents a new state-space method for spectral estimation that performs decimation by any factor, it makes use of the full set of data and brings further apart the poles under consideration, while imposing almost no constraints to the size of the Hankel matrix (model order), as decimation increases. It is compared against two previously proposed techniques for spectral estimation (along with derived decimative versions), that lie among the most promising methods in the field of spectroscopy, where accuracy of parameter estimation is of utmost importance. Moreover, it is compared against a state-of-the-art purely decimative method proposed in literature. Experiments performed on simulated NMR signals prove the new method to be more robust, especially for low signal-to-noise ratio.

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