Fast robust image moving deblurring method based on splitting Bregman iteration

A motion blurring and deblurring technology, applied in image enhancement, image data processing, instruments, etc., can solve the problem of high computational complexity

Active Publication Date: 2014-09-10
NANJING UNIV OF POSTS & TELECOMM
View PDF5 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The mean field variational approximation method can estimate the mo

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
  • Fast robust image moving deblurring method based on splitting Bregman iteration
  • Fast robust image moving deblurring method based on splitting Bregman iteration
  • Fast robust image moving deblurring method based on splitting Bregman iteration

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] Such as Figure 1-5 As shown, the present invention discloses a fast and robust image motion deblurring method based on split Bregman iteration, and the specific steps are:

[0058] First, by directly using the image gradient with the motion blur kernel's L 0 Norm and combine the image gradient with the motion blur kernel for the respective L 2 Norm, constructing a non-convex and non-smooth energy functional for motion blur kernel estimation;

[0059] Secondly, by coupling operator splitting and augmented Lagrangian method, the split Bregman iterative solution format of motion blur kernel is designed;

[0060] Finally, a non-blind image deblurring method based on total variation prior is used to achieve fast image deblurring.

[0061] Concrete implementation steps of the present invention:

[0062] (1) Given the image y to be motion deblurred, the size of the motion blur kernel h to be estimated is Z×Z;

[0063] (2) In order to avoid the fuzzy kernel estimation fro...

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 belongs to the field of digital image processing, and provides a fast robust image moving deblurring method based on splitting Bregman iteration. According to the method, a nonconvex nonsmooth energy functional for moving fuzzy kernel estimation is constructed through directly utilizing the image gradient and the L0 normal number of a moving fuzzy kernel and combining respective L2 normal numbers; a splitting Bregman iteration computational scheme of the moving fuzzy kernel is designed by coupling operator splitting and augmented Lagrangian methods; and the fast deblurring of images is realized by adopting an image non-blind deblurring method based on total variation priors. The fast robust image moving deblurring method has the advantages that through the introduction of support continuity priors, the estimation precision of the moving fuzzy kernel is improved; and a novel fast solution based on the splitting Bregman iteration is designed, and the estimation efficiency of the moving fuzzy kernel is greatly improved.

Description

technical field [0001] The invention belongs to the field of digital image processing, and in particular relates to a method for automatically estimating a point spread function (point spread function) or a motion blur kernel (motion blurkernel) corresponding to various random shakes of a camera by using a single blurred image captured by a camera. Background technique [0002] During the camera shooting process, the random camera shake caused by some uncontrollable factors often leads to motion blur in the captured image. The most typical situation is the random shake that occurs when the camera is exposed for a long time in a low-light environment. [0003] The technical core of processing motion blur images is to automatically estimate the point spread function corresponding to various random shakes of the camera. At present, most point spread function estimation methods are based on the Bayesian statistical framework. According to different inference criteria, they are m...

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): G06T5/40G06T5/00
Inventor 邵文泽葛琦朱虎谢世朋成孝刚李海波
Owner NANJING UNIV OF POSTS & TELECOMM
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