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

Self-adaption moment matching stripe noise removing method based on gray-level segmentation

A stripe noise, grayscale segmentation technology, applied in image enhancement, instrumentation, computing and other directions, to achieve the effect of improving image quality and high operating efficiency

Active Publication Date: 2012-12-12
WUHAN UNIV
View PDF3 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The problem to be solved by the present invention is to provide an effective image noise removal method for the random band noise existing in panchromatic images

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-adaption moment matching stripe noise removing method based on gray-level segmentation
  • Self-adaption moment matching stripe noise removing method based on gray-level segmentation
  • Self-adaption moment matching stripe noise removing method based on gray-level segmentation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] According to the basic theory of image processing, it can be known that different peaks of the image histogram represent different types of features contained in the image. Although the standard moment matching method will cause grayscale distortion when processing images with rich features, that is, in the image histogram When there are multiple peaks or the span of the histogram peak curve is large, the standard moment matching method will cause grayscale distortion, but for the curve distribution of a single peak with a small grayscale range When performing noise removal processing, it will not cause grayscale distortion in the image. Therefore, the imaging data inside a single detector is distinguished according to the difference in the image histogram distribution (that is, different gray levels), and then the variance and mean of the imaging data in different gray areas are calculated, and finally the different gray areas The imaging data is processed by standard ...

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-adaption moment matching stripe noise removing method based on gray-level segmentation, which comprises the following steps: acquiring a brightness value curve for an original noise-containing image; performing median filtering on the brightness value through processing windows with different sizes for removing a base line, and acquiring processing unit centers; adjusting according to the distance between each two adjacent processing unit centers to confirm a processing unit; and performing image processing on single processing unit with the processing way of matching in standard moment. For remote sensing panchromatic images with large data size, an effective noise removing method for the image is provided. The method provided by the invention can effectively recover the image and improve the image quality and has high algorithmic efficiency.

Description

technical field [0001] The invention belongs to the field of remote sensing image processing, and relates to an adaptive moment matching strip noise removal method based on gray scale segmentation. Background technique [0002] Banding noise is an important factor that affects the imaging quality of optical satellite images. Suppressing or removing banding noise is one of the basic links in satellite ground preprocessing for radiation processing. Due to the interference of internal and external factors in the imaging system of optical satellites, such as: the performance of CCD devices (charge-coupled devices) changes over time, atmospheric interference, etc., there will still be bands in the image after image homogenization and relative radiation correction Noise, the existence of this kind of noise, greatly reduces the clarity of the image and increases the difficulty for the subsequent interpretation and processing of the image, so it must be eliminated. [0003] Through...

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): G06T5/00G06T5/40
Inventor 王密张炳先潘俊李德仁
Owner WUHAN 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