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

A Star Map Deblurring Method Based on Improved rl Deconvolution Algorithm

A deblurring and deconvolution technology, applied in computing, image enhancement, image analysis, etc., can solve problems such as poor real-time performance and poor image robustness, and achieve the effect of suppressing image blur and improving real-time performance

Active Publication Date: 2022-02-11
SOUTHEAST UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Purpose of the invention: In order to overcome the deficiencies of the prior art, the present invention provides a star map deblurring method based on the improved RL deconvolution algorithm, which overcomes the poor real-time performance and the deblurring after deblurring caused by the artificial experience setting parameters of the traditional RL deconvolution algorithm. The problem of poor image robustness of

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 Star Map Deblurring Method Based on Improved rl Deconvolution Algorithm
  • A Star Map Deblurring Method Based on Improved rl Deconvolution Algorithm
  • A Star Map Deblurring Method Based on Improved rl Deconvolution Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0024] Such as figure 1 As shown, the present invention discloses a star map deblurring method of an improved Richardson-Lucy (RL) deconvolution algorithm, comprising the following steps:

[0025] (1) In the star map simulator, set the field of view of the star sensor to 20°×20°, the focal length of the CMOS camera to 98.8mm, the CMOS area array to 512×512, the pixel width to 26μm, the pixel height to 26μm, and the star gray The degree value is 100, the star size is 4 pixel values, and it is set to randomly add false stars and random missing stars in the star map. The motion trajectory of the star sensor is simulated by the orbit generator, and a large number of clear stars are simulated using the above parameters. There is no specific requirement for the number of pictures, generally hundreds or thousands of pictures are simulated, and the star sensor dithering item is added to the above settings to simulate the corresponding fuzzy star map.

[0026] (2) Calculate the point ...

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 star map deblurring method based on an improved RL deconvolution algorithm, comprising: (1) setting basic simulation parameters in a star map simulator, using the basic simulation parameters to simulate a clear star map and corresponding fuzzy stars; (2) calculate the point spread function of each fuzzy star map according to the inertial sensor element data; (3) use the RL deconvolution algorithm to complete the defuzzification of the star map, and record the optimal number of iterations and iteration steps of the deblurring effect (4) The point spread function, number of iterations and iteration step of each blurred image are used as input for offline training of the neural network prediction model. After the training is completed, the prediction model is obtained, and the output is the number of iterations and the iteration step. The invention overcomes the disadvantage that the traditional RL deconvolution defuzzification algorithm needs to manually test the number of iterations and iteration steps to complete the defuzzification of the star map, improves the real-time performance of the algorithm and significantly improves the effect of the star map defuzzification.

Description

technical field [0001] The invention relates to a star map defuzzification method, in particular to a star map defuzzification method based on an improved RL deconvolution algorithm. Background technique [0002] The blurring of the star map is caused by the relative motion between the photosensitive medium and the starry sky at the moment of exposure. The limited starlight energy is scattered on more pixels, resulting in blurred star images and inaccurate positioning of the center of mass. For image motion compensation, there are currently mechanical, optical, electronic, and image image motion compensation methods. [0003] The image-based image motion compensation method is to restore the blurred star map to complete the image motion compensation, and it is also a compensation method for CMOS cameras. Different from mechanical, optical, and electronic methods, the image-based image motion compensation method performs post-processing on the generated digital image to eli...

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): G06T5/00
CPCG06T5/003G06T2207/10004G06T2207/20084G06T2207/20081
Inventor 陈熙源柳笛方文辉方琳
Owner SOUTHEAST 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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com