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Initial method for image independent component analysis

A technology of independent component analysis and initialization method, applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problems of reducing the convergence speed of the algorithm, reducing the separation accuracy of the algorithm, affecting the real-time performance of the algorithm, etc., to improve the convergence speed, The effect of improving separation accuracy and accelerating algorithm convergence

Inactive Publication Date: 2007-03-21
SHANGHAI UNIV
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Problems solved by technology

[0004] Randomly selecting the initial value of a variable (such as the mixing matrix in the FastICA algorithm) in the ICA algorithm may cause the algorithm to fall into a local minimum and increase the number of iterations during convergence, resulting in a decrease in the separation accuracy of the entire algorithm and a reduction in the convergence speed of the algorithm. Affect the real-time performance of the algorithm

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  • Initial method for image independent component analysis
  • Initial method for image independent component analysis
  • Initial method for image independent component analysis

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Embodiment Construction

[0036] A preferred embodiment of the present invention is described as follows in conjunction with accompanying drawing:

[0037] The initialization method of this independent component analysis is shown in Figure 1. Firstly, the wavelet sparse decomposition is performed on the received mixed signal, and then the most sparse decomposition coefficient group is selected, and the clustering method is used to find the polyaxis in its star map to estimate the mixing matrix. Finally, the estimated value of this mixing matrix is ​​used to initialize the FastICA algorithm, avoiding the local minimum when the ICA method converges, speeding up the algorithm convergence, and improving the separation accuracy of the ICA method, and achieving the ideal image separation effect.

[0038] The specific steps are:

[0039] ①Initialize the maximum number of decomposition layers N L ;

[0040] ② Using wavelet transform, for the received signal X(t)=[x 1 (t), x 2 (t), L, x M (t)] T Perform ...

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Abstract

An initialization method for image independent component analysis, it is: processes wavelet sparse decomposition for the receiving mixed signal; selects the decomposed coefficient group with the best sparseness, seeks the gather-axis to estimate the mixed matrix by the clustering method in the star-chart; processes initialization to the FastICA arithmetic by the estimating value of the mixed matrix, in order to avoid the minimum partly when the independent component analysis method, expedites the arithmetic constringency, simultaneously improves the separation precision of the independent component analysis method, gets the perfect image separating effect. The invention is fit for the radio-communication system, the sonar and radar system, the audio and acoustics signal process of the military field and non- military field.

Description

technical field [0001] The invention relates to an image noise reduction method, in particular to an initialization method for image independent component analysis. It has important application potential in image signal processing in military or non-military fields. Background technique [0002] Usually, the image will be polluted by other signals during its acquisition or transmission process, and it is necessary to carry out separation processing for subsequent further processing. The purpose of image separation is to extract the individual signal components in the received signal as much as possible to improve the quality of the image. At present, image noise reduction methods are mainly divided into traditional filtering methods and blind source separation methods, among which blind source separation methods are the most representative. [0003] The blind source separation method is to separate these mutually independent source signals only through the received mixed s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/40
CPCG06K9/6242G06F18/21342
Inventor 刘盛鹏方勇
Owner SHANGHAI UNIV
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