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KPCA reconstruction method and system based on convex set projection

A technology of convex set projection and projection coefficient, which is applied in the field of KPCA reconstruction method and system based on convex set projection, can solve the problems of unstable calculation and high reconstruction error, and achieve the effect of small root mean square error and stable performance

Pending Publication Date: 2022-01-11
深圳市鸿逸达科技有限公司
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Problems solved by technology

In the traditional KPCA method, because the reciprocal of the eigenvalue is involved in the reconstruction, there are problems such as unstable calculation and high reconstruction error.

Method used

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  • KPCA reconstruction method and system based on convex set projection
  • KPCA reconstruction method and system based on convex set projection
  • KPCA reconstruction method and system based on convex set projection

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Embodiment Construction

[0011] Embodiments of the present invention are described below with reference to the accompanying drawings, so that those skilled in the art can better understand the present invention and implement it, but the enumerated embodiments are not used as a limitation of the present invention. In the case of no conflict, The following embodiments and the technical features in the embodiments can be combined with each other, wherein the same components are denoted by the same reference numerals.

[0012] The method of the present invention is applicable to data of any dimension, and can be applied to image or video data, such as an image with a size of 300x200 (which can be understood as data with a dimension of 60,000). The following uses an image as an example to illustrate the specific steps of the present invention. This step can also be applied to data of any other dimension.

[0013] Through steps S1 and S2, a compressed image can be obtained.

[0014] Step S1: For the image...

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Abstract

The invention provides a KPCA reconstruction method based on convex set projection. The method comprises the following steps: acquiring an initial value of a transform domain kernel function vector of data; based on the initial value of the kernel function vector, repeating the following iterations to obtain a reconstruction value of the kernel function vector: performing non-negative operation element by element to meet a non-negative limit; fixing an expansion component based on the truncation transformation matrix to meet a truncation component limit; and outputting a reconstruction result of the data based on the reconstruction value of the kernel function vector. According to the method, the stability and the performance of data reconstruction are greatly improved.

Description

technical field [0001] The present invention relates to data compression technology, more specifically, to a KPCA reconstruction method and system based on convex set projection. Background technique [0002] With the development of artificial intelligence technology, the classification and recognition technology for pictures and videos is widely used, and the amount of data processing is also increasing. Therefore, new high requirements are put forward for data compression technology. Among them, the Kernel Principal Components Analysis (KPCA) method is based on the principal component analysis method (PCA), with the help of nuclear domain transformation, to realize the principal component analysis under nonlinear high-dimensional mapping, in data dimension reduction, compression, background extraction have a wide range of applications. In the traditional KPCA method, because the reciprocal of the eigenvalue is involved in the reconstruction, there are problems such as uns...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/77G06V10/774
CPCG06F18/2135G06F18/214
Inventor 邵肖伟许永伟
Owner 深圳市鸿逸达科技有限公司