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

Multiframe iteration blind deconvolution image restoration method based on anisotropic constraint

An anisotropic, image-based technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as slow convergence speed and noise sensitivity of image restoration methods

Inactive Publication Date: 2011-05-18
耿则勋
View PDF1 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The principle of this image restoration method is simple, and it can deal with image degradation caused by many different types of PSF. At the same time, in the iterative process, it does not require other prior knowledge except for the assumption that the PSF and the gray value of the image are non-negative; however, the image restoration method Slow to converge and very sensitive to noise

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
  • Multiframe iteration blind deconvolution image restoration method based on anisotropic constraint
  • Multiframe iteration blind deconvolution image restoration method based on anisotropic constraint
  • Multiframe iteration blind deconvolution image restoration method based on anisotropic constraint

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The technical solution of the present invention will be described in detail below with examples: the principle, processing process and experimental results of the multi-frame iterative blind deconvolution image restoration method based on anisotropy constraints are given respectively.

[0038] Assuming that in actual observation, the formation process of the image is linear or space-invariant, and the observation image noise is mainly additive noise, which is independent of the observation target, the imaging model of the observation image can be expressed as:

[0039]

（1’）

[0040] in, , Represents a two-dimensional linear convolution, is the degraded image actually acquired, ideal image for the target, is the point spread function, Indicates the additive noise mixed in the imaging process.

[0041] For multi-frame observation images of the same target, there are:

[0042]

（2’）

[0043] Among them, the subscript...

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 provides a multiframe iteration blind deconvolution image restoration method based on anisotropic constraint, in which the anisotropic regularization thought is introduced into an image restoration process. The method can be used for restoring the high definition image of a observation target by the complementary information of an observation image, the image grey level, the non-negativity restrictions of a point spread function and the support region constraint of the point spread function only according to the multiframe reduced-quality image of the obtained observation target under the condition of providing no prior information about the point spread function. In the restoration process, with the method, the self structural information of the image can be effectively utilized to self-adaptively adjust an anisotropic regularization parameter according to the local characteristic and the noise immunity of an algorithm can be improved while the image edge information is kept.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to image restoration technology, in particular to the technical field of image restoration of astronomical point source stars and astronomical extended objects in photoelectric imaging observation and identification of astronomical targets. Background technique [0002] In order to provide a basis for the study of the evolution of cosmic stars and at the same time provide support for the analysis of the external shape and geometric structure of astronomical extended objects, people use the existing ground-based photoelectric imaging equipment to obtain a large number of images of astronomical stars and astronomical extended objects. However, since these images are obtained through the earth's atmosphere through ground-based photoelectric telescopes, the randomly changing turbulent structure of the earth's atmosphere will blur and degrade the imaging, which seriously affects th...

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
IPC IPC(8): G06T5/50
Inventor 耿则勋宋向王洛飞魏小峰陈路杨阳娄博
Owner 耿则勋
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