Image deblurring method based on genetic algorithm and Wiener filtering

A Wiener filter and genetic algorithm technology, applied in the field of computer image processing, can solve the problems of image restoration not fully satisfied, premature convergence, low computational efficiency and so on

Inactive Publication Date: 2017-01-04
GUANGXI NORMAL UNIV
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The Wiener filtering algorithm is simple, and it uses the minimum mean square error criterion to avoid the phenomenon of excessive noise, but the signal required by the algorithm is a stationary random process, which is quite different from the actual situation of image blurring. The results of image restoration are not entirely satisfactory
However, although the single application of genetic algorithm has good robustness, there will be problems such as premature convergence and low computational efficiency.

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
  • Image deblurring method based on genetic algorithm and Wiener filtering
  • Image deblurring method based on genetic algorithm and Wiener filtering
  • Image deblurring method based on genetic algorithm and Wiener filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0040] refer to figure 1 , an image deblurring method based on genetic algorithm and Wiener filtering, comprising the following steps:

[0041] 1) Encoding the chromosome and randomly generating the initial population: using 8-bit binary coding, randomly generating the binary string to form the genetic code of the chromosome, and generating a population consisting of a preset number of 10 individuals as the parent generation;

[0042] 2) Calculate the fitness value of each individual: quote the signal-to-noise ratio SNR as the fitness function to evaluate the individual, and calculate the fitness value of each individual in the population;

[0043] 3) Genetic operation to find k when the fitness converges: select excellent individuals from the population obtained in step 1), and replace the parent body with individuals with strong fitness through selection, crossover, and mutation of genetic operations, and eliminate inferior individuals. Until the specified preset terminatio...

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 image deblurring method based on genetic algorithm and Wiener filtering. The method comprises the following steps: 1. encoding chromosomes and randomly generating an initial population; 2. calculating the suitability value of each individual; 3. conducting genetic operation to revolve K value upon convergence of the suitability: selecting excellent individuals from the population which is obtained from step 1, replacing paternal bodies with the individuals that have strong suitability by performing selection, crossing and variation according to the genetic operations, eliminating inferior individuals until a designated termination of algebra has reached, at which time the suitability value K is the optimal value; 4. returning a regularization term k to a Wiener filtering; and 5. using Wiener filtering to deblur a an image: firstly establishing an image deblurring model, then using the Wiener filtering to resolve the result of the image deblurring at the moment, and outputting the deblurred image and the signal-to-noise ratio at the moment. The method is based on genetic algorithm and the regularization term of the Wiener filtering power ratio, avoids too early convergence and increases signal-to-noise ratio of the image.

Description

technical field [0001] The invention relates to computer image processing technology, in particular to an image deblurring method based on genetic algorithm and Wiener filtering. Background technique [0002] Blurring of digital images is a common result of sharpening. The process of deblurring is the process of restoring the desharpened image to clarity. Atmospheric airflow, relative movement between the subject and the camera, misfocus of the lens, etc. may all produce blurred images. [0003] Blurred images generally include motion blur (Motion Blur) and defocus blur (Defocus blur). The blurred image can be expressed as the convolution of the original image and the point spread function plus noise. In the process of image deblurring and restoration, according to whether the blur kernel is known or not, it can be divided into two types: blind deconvolution (Blind deconvolution) and non-blind deconvolution (non-blind deconvolution). Among the non-blind deconvolution met...

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): G06T5/00G06N3/12
CPCG06N3/126G06T5/73
Inventor梁晓萍罗晓曙
OwnerGUANGXI NORMAL UNIV