Multi-attribute volume data compression method based on high-order tensor approximation

A compression method and multi-attribute technology, applied in image data processing, 3D image processing, instruments, etc., to achieve the effect of reducing the compression rate

Active Publication Date: 2020-09-01
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

To reduce the redundant information in these data, the traditional third-order tensor approximation cannot solve

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-attribute volume data compression method based on high-order tensor approximation
  • Multi-attribute volume data compression method based on high-order tensor approximation
  • Multi-attribute volume data compression method based on high-order tensor approximation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0032] Such as figure 1 Shown is a schematic flowchart of the multi-attribute volume data compression method based on high-order tensor approximation of the present invention. A multi-attribute volume data compression method based on high-order tensor approximation, comprising the following steps:

[0033] A. Preprocess the multi-attribute body data, and divide each attribute body into block data of the same size;

[0034] B. Represent the block data in step A as a high-order tensor, perform low-rank decomposition on the high-order tensor, and obtain a factor matrix and a core tensor;

[0035] C...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a multi-attribute volume data compression method based on high-order tensor approximation. It includes preprocessing multi-attribute volume data, decomposing high-order tensors of block data into factor matrices and core tensors, and obtaining approximate high-order tensors according to the reconstruction of factor matrices and core tensors. For each The attribute volume is fused and drawn to complete the multi-attribute volume data compression. The invention greatly reduces the compression rate of the tensor approximation, and at the same time retains the original data of the multi-attribute body, effectively reflecting the target characteristics of the data.

Description

technical field [0001] The invention belongs to the technical field of data compression, in particular to a multi-attribute volume data compression method based on high-order tensor approximation. Background technique [0002] In today's scientific research and production, people hope to present and interpret data in an intuitive and fast way. Therefore, data visualization has become a very important means of data research and analysis. After continuous development, an interdisciplinary field-scientific visualization was finally formed: using images to help people understand scientific and technological concepts and the results expressed by complex and large-scale data. Scientific visualization technology can effectively connect and bring out human vision and perception, and intuitively express the distribution and characteristics of data itself, especially the visualization of three-dimensional data. Among them, volume rendering technology, as an important means of data v...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06T9/00G06T15/08
CPCG06T9/00G06T15/08
Inventor 鲁才陈婉彭立宇胡光岷
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products