A method of eliminating defocus noise in optical scanning holography based on self-organizing map neural network

A technology of self-organizing mapping and neural network, which is applied in the field of eliminating defocus noise in optical scanning holography, can solve problems such as low timeliness, deformation, and rough edges of results, and achieve the effects of easy operation, short training time, and simple implementation

Inactive Publication Date: 2019-08-09
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The document "Sectional image reconstruction in optical scanning holography using a random-phase pupil" proposes an algorithm for encrypting optical scanning holograms by using random phase plates, and proposes a method to eliminate defocus noise by using multi-frame averaging. The method can eliminate defocus noise very well, but due to the need for multi-frame averaging processing, the timeliness is low
[0005] The document "Defocus noise suppression with combined frame difference and connected component methods in optical scanning holography" proposes a method based on frame difference method and connected domain. This method has good timeliness, but the edge of the result obtained by this method is not smooth. And it is deformed compared with the original image

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
  • A method of eliminating defocus noise in optical scanning holography based on self-organizing map neural network
  • A method of eliminating defocus noise in optical scanning holography based on self-organizing map neural network
  • A method of eliminating defocus noise in optical scanning holography based on self-organizing map neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] Such as Figure 1 to Figure 6 As shown, the method for eliminating optical scanning holographic defocus noise based on self-organizing map neural network, the specific steps are as follows:

[0062] (S100) Obtaining an encrypted hologram by scanning the object with an optical holographic scanning device:

[0063] The basic structure of the optical holographic scanning device used is as follows: figure 1 As shown, it includes: the laser Laser, the first beam splitter BS1 corresponding to the laser Laser, the acousto-optic modulator AOFS, the first mirror M1, the first pupil p 1 (x, y) and the first optical path formed by the first convex lens L1 and corresponding to the first beam splitter BS1, the second mirror M2, the second pupil p 2 (x, y) and the second convex lens L2 constitute the second optical path corresponding to the first beam splitter BS1, the second beam splitter BS2 that combines the first optical path and the second optical path by interference, and the...

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 method for eliminating defocus noise in optical scanning holography based on a self-organizing mapping neural network, which belongs to the fields of optical scanning holography and image denoising, and mainly solves the problem of defocus noise in optical scanning holography. The invention utilizes the clustering analysis capability of the self-organizing map neural network to eliminate the defocus noise of the reconstructed image after random encryption processing. The invention can effectively solve the problem of defocus noise in optical scanning holography, and the noise removal method is applicable to various fields.

Description

technical field [0001] The present invention relates to the fields of optical scanning holography and image denoising, in particular to a method for eliminating defocus noise of optical scanning holography based on a self-organizing mapping neural network and a device for realizing the method. Background technique [0002] Optical scanning holography, or OSH for short, is a recording technology that can record 3-D holographic information by using a single 2-D optical heterodyne scan. Since the technology was proposed, it has been applied in many fields, such as 3-D microscopy, 3-D pattern recognition, and holographic image encryption. [0003] Eliminating defocus noise has always been a hot research issue in optical scanning holography, and it is of great significance for holograms of multi-layer slices. When the reconstructed hologram is focused on a certain layer, the other layers will affect the clarity of the image as defocus noise. Therefore, in order to obtain a high-...

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): G03H1/00G03H1/12G06T5/00G06K9/62G06N3/04G06N3/08
CPCG03H1/0005G03H1/12G06N3/088G06T5/002G06T2207/20081G06T2207/20084G06N3/045G06F18/23
Inventor 欧海燕刘柯邵维王秉中
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap