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

Self-adaptive non-local mean filtering method for salt and pepper noise

A non-local average and salt-and-pepper noise technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as inability to guarantee, achieve excellent denoising effect, expand application range, and improve performance

Pending Publication Date: 2022-01-28
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing salt and pepper noise removal methods cannot guarantee to obtain high-quality images stably and efficiently under the conditions of different images and different noise intensities

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
  • Self-adaptive non-local mean filtering method for salt and pepper noise
  • Self-adaptive non-local mean filtering method for salt and pepper noise
  • Self-adaptive non-local mean filtering method for salt and pepper noise

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The noise model in the prior art is: define the pixel matrix of the original image as y, the position of any point in the image is marked as (i, j), and the pixel of any point is marked as y i,j . Similarly, define the pixel matrix of the noise image as x, the position of any point in the image is recorded as (i, j), and the pixel of any point is recorded as x i,j . Then, for a given image with noise density p ∈ (0, 1), we have It can also be expressed in more detail as, where gamma 1 Determines whether a pixel is polluted, γ 2 Determine whether the polluted pixels are salt noise or pepper noise.

[0045]On the basis of the above-mentioned salt and pepper noise model, the present invention proposes a new denoising method. The method is divided into two steps: the first step, preliminary estimation filtering. In the second step, the noise is further reprocessed using a non-local mean method with adaptive parameters. In the preliminary estimation filtering proce...

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 relates to a self-adaptive non-local mean filtering method for salt and pepper noise, and belongs to the technical field of digital image processing. The invention provides a simple and effective method for removing salt and pepper noise. Firstly, a sliding window is used to identify noise points, and local filtering is used to carry out preliminary denoising. Secondly, non-local mean filtering with adaptive parameters is provided for secondary denoising; a smoothing parameter is designed as a piecewise function according to the intensity level of the salt and pepper noise. Experimental results on a public data set show that the novel filter balances the relationship between the denoising effect and the consumed time. Moreover, the novel filter can effectively restore the pixels of a polluted image and retain the texture details of the image.

Description

technical field [0001] The invention relates to an adaptive non-local mean filtering method for salt and pepper noise. It belongs to the technical field of digital image processing. Background technique [0002] Digital images are often affected by imaging equipment and external environment interference during quantization and transmission. Noise often reduces the quality of the image and has an adverse effect on subsequent image processing (such as segmentation, compression, and information extraction, etc.). In order to suppress noise and improve image quality, it is necessary to remove noise from the image. There are many types of noise, one of which is salt and pepper noise, also known as impulse noise. This noise manifests as randomly generated dots with either 0 or 255 pixels. [0003] In the process of image acquisition, problems such as pixel failure in the camera sensor, wrong storage location in the hardware, and noisy channels for transmitting data often lead ...

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 Applications(China)
IPC IPC(8): G06T5/20G06T5/00
CPCG06T5/20G06T2207/20032G06T2207/20024G06T5/70
Inventor 刘书刚马昕玥
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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