Vehicle Information Bus Image Restoration Using Multi-wavelet Transform Constant Module Blind Equalization Algorithm

2013 ◽  
Vol 5 (10) ◽  
pp. 107-114
Author(s):  
Zhuangwen Wu ◽  
Liangrong Zhu
Keyword(s):  
Wavelet Transform ◽  
Image Restoration ◽  
Blind Equalization ◽  
Equalization Algorithm ◽  
Vehicle Information

Orthogonal Wavelet Transform Blind Equalization Algorithm Based on the Optimization of Artificial Fish Swarm Algorithm

2012 ◽  
Vol 198-199 ◽  
pp. 1399-1402
Author(s):  
Wei Huang ◽  
Ye Cai Guo
Keyword(s):  
Wavelet Transform ◽  
Convergence Rate ◽  
Blind Equalization ◽  
Weight Vector ◽  
Orthogonal Wavelet ◽  
Artificial Fish Swarm Algorithm ◽  
Equalization Algorithm ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Orthogonal Wavelet Transform

According to disadvantages of big steady-state error, low convergence rate, and local convergence of traditional Constant Modulus blind equalization Algorithm (CMA), an orthogonal Wavelet Transform blind equalization Algorithm based on the optimization of Artificial Fish Swarm Algorithm(AFSA-WT-CMA) is proposed. In this proposed algorithm, the weight vector of the blind equalizer is regarded as artificial fish, the equalizer weight vector can be optimized via making full use of global search and information sharing mechanism of artificial fish school algorithm, the de-correlation ability of normalizing orthogonal wavelet transform. The computer simulations in underwater acoustic channels indicate that the proposed algorithm outperforms CMA and WT-CMA in convergence rate and mean square error.

Research on Realization of Medical Image Restoration Based on Blind Equalization Algorithm

2020 ◽  
Vol 10 (4) ◽  
pp. 809-813
Author(s):  
Ting Han ◽  
Ruo-Han Zhao ◽  
Mo Dong
Keyword(s):  
Image Restoration ◽  
Medical Image ◽  
Medical Images ◽  
Blind Equalization ◽  
Diagnostic Errors ◽  
Degradation Process ◽  
Restoration Algorithm ◽  
Equalization Algorithm ◽  
Improvement Effect ◽  
Blind Restoration

In order to study the realization of medical image restoration, this study mainly adopts blind equalization algorithm to analyze medical images, and observes the improvement effect of blind equalization technology on medical images. In the process of medical image formation, it is unavoidable to be affected by point spread function, which leads to image degradation and brings great difficulties to diagnosis, and the results of degradation are often unpredictable. The results show that the blind restoration algorithm can restore the image when the degradation process of the medical image is uncertain, which makes the medical image clearer and more accurate, brings great convenience to the diagnosis, and also reduces the diagnostic errors caused by the unclear image.

Double Error Function Decision Feedback Momentum Blind Equalization Algorithm

2011 ◽  
Vol 328-330 ◽  
pp. 2097-2101
Author(s):  
Li Kun Xing ◽  
Long Wu ◽  
Ye Cai Guo
Keyword(s):  
Wavelet Transform ◽  
Error Function ◽  
Blind Equalization ◽  
Decision Feedback ◽  
Improve Performance ◽  
Orthogonal Wavelet ◽  
Equalization Algorithm ◽  
Convergence Performance ◽  
Simulation Results ◽  
Orthogonal Wavelet Transform

Against the shortcomings of slow convergence and large residual error in norm decision feedback blind equalization, double error function decision feedback blind equalization algorithm based on orthogonal wavelet transform momentum (WT-DMCMA-DFE)was proposed. In the algorithm, the four combinations of two error functions, respectively, to make adjustments on the former right and the feedback right, and add momentum algorithm to the former right and the feedback right to accelerate the convergence rate, escape correlation by using the orthogonal wavelet transform and normalize the energy to further improve performance of the convergence. Underwater acoustic channel simulation results show that convergence performance and mean square error of WT-MCMA-DFE, WT-H-HMCMA-DFE, WT-H-CMCMA-DFE is different.

Application of Constraint CMA Blind Equalization Algorithm in the Medical Image Restoration

2012 ◽  
Vol 263-266 ◽  
pp. 2109-2112
Author(s):  
Jin Zhang ◽  
Ya Jie Mao ◽  
Li Yi Zhang ◽  
Yun Shan Sun
Keyword(s):  
Image Restoration ◽  
Cost Function ◽  
Medical Image ◽  
Signal To Noise Ratio ◽  
Blind Equalization ◽  
Optimal Solution ◽  
The Novel ◽  
Constant Modulus ◽  
Signal To Noise ◽  
Equalization Algorithm

A constraint constant module blind equalization algorithm for medical image based on dimension reduction was proposed. The constant modulus cost function applied to medical image was founded. In order to improve the effect of image restoration, a constraint item was introduced to restrict cost function, and it guarantees that the algorithm converge the optimal solution. Compared to the traditional methods, the novel algorithm improves peak signal to noise ratio and restoration effects. Computer simulations demonstrate the effectiveness of the algorithm.

scholarly journals Neural Network Blind Equalization Algorithm Applied in Medical CT Image Restoration

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yunshan Sun ◽  
Liyi Zhang ◽  
Jin Zhang ◽  
Lijuan Shi
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Blind Equalization ◽  
Ct Image ◽  
Original Image ◽  
Equalization Algorithm ◽  
Convergence Performance ◽  
And Performance ◽  
Blind Image ◽  
Method Analysis

A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived and used in conjunction with Zigzag coding to restore the original image. As a result, the effect of PSF can be removed by using the proposed algorithm, which contributes to eliminate intersymbol interference (ISI). In order to obtain the estimation of the original image, what is proposed in this method is to optimize constant modulus blind equalization cost function applied to grayscale CT image by using conjugate gradient method. Analysis of convergence performance of the algorithm verifies the feasibility of this method theoretically; meanwhile, simulation results and performance evaluations of recent image quality metrics are provided to assess the effectiveness of the proposed method.

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