Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Super-sparse cs fusion method applied to structured light images

A fusion method and structured light technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low precision, slow speed, lack of information and high requirements for image sampling, and achieve the effect of improving operation fluency and efficiency

Active Publication Date: 2019-06-25
SHENYANG POLYTECHNIC UNIV
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problems of low speed and low precision of the current structured light imaging system and high requirements for image sampling with lack of information

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
  • Super-sparse cs fusion method applied to structured light images
  • Super-sparse cs fusion method applied to structured light images
  • Super-sparse cs fusion method applied to structured light images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] Below in conjunction with accompanying drawing, the present invention will be further described:

[0042] Aiming at the problem of increasing the speed, a compressed sensing fusion method of undersampling, fast sampling, fast fusion and efficient restoration is proposed.

[0043] Compressed sensing theory solves the problem of massive data processing under the fusion rule of pixel maximization.

[0044] The super-sparse CS fusion method applied to structured light images, the implementation process of this method is divided into the following five steps:

[0045] Step 1: When the images captured by the structured light equipment are multiple images with unclear details or missing details, transfer the images to the computer; figure 1 As shown, the structured light equipment includes a stage 1, an irradiation stage 2 and a guide rail. The irradiation stage 2 is located above the stage 1. The lower end surface of the irradiation stage 2 is provided with two lenses 3 faci...

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 an ultra-sparse CS fusion method applied to structured light images. Step 1: When the images captured by a structured light device are multiple images with unclear details or missing details, the images are transmitted to a computer; Step 2: Decompose each image by wavelet; step 3: perform compressed sensing compression on the larger wavelet coefficients decomposed under the compressed sensing framework, and fuse the compressed ultra-sparse coefficients by maximizing the absolute value; the fusion base is selected using the coif4 wavelet base ; Step 4: Through the orthogonal matching pursuit method and iterative calculation, the CS image restoration after super-sparse coefficient fusion is realized; Step 5: The restored image is transmitted back to the institutional optical imager through electrical signals for continued mechanical operation. It realizes under-sampling under the condition of signal sparse or nearly sparse, and then restores the defective structured light image with high probability through the best fusion method based on compressed sensing.

Description

technical field [0001] The invention relates to the field of image undersampling fusion processing, in particular to an ultra-sparse CS fusion method applied to structured light images. Background technique [0002] The current imaging methods of structured light imaging are often restricted by some factors. For example, the imaging method based on Fourier fringe analysis is very suitable for dynamic scenes because it only needs to acquire one frame of image to reconstruct the surface shape of the measured object. However, its disadvantages are concentrated in the large amount of calculation, and factors such as frequency domain mixing and leakage make the error larger. In the past two years, some scholars have proposed a structured light illumination fluorescence microscopy imaging system, which has significantly improved the imaging speed and image resolution. However, in order to further improve the calculation accuracy, more complex algorithms must be considered and mo...

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): G06T5/50G06T5/00
CPCG06T5/50G06T2207/20064G06T2207/20221G06T5/00
Inventor 任建秦龙博王福强李邦宇刘斌
Owner SHENYANG POLYTECHNIC UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products