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

Image processing method based on adaptive plip model

An image processing and self-adaptive technology, applied in the field of image processing, which can solve the problems of loss of details and uneven brightness of the result image, and achieve the effects of uniform brightness, improved average brightness, and improved accuracy.

Active Publication Date: 2021-01-05
XIDIAN UNIV
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art, and propose an image processing method based on the adaptive PLIP model, which is used to solve the loss of details and uneven brightness of the resulting image in the prior art when natural images are enhanced. The problem

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 processing method based on adaptive plip model
  • Image processing method based on adaptive plip model
  • Image processing method based on adaptive plip model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] refer to figure 1 The present invention is further described.

[0038] Step 1, obtain the luminance component map of the image to be processed.

[0039] Input a natural image to be processed, if the image is a color image, convert the image from the red, green and blue RGB color space to the hexagonal pyramid HSV color space, and extract the image from the hexagonal pyramid HSV color space The brightness component of the image is obtained to obtain the brightness component map of the image to be processed, and divide the brightness component map into even blocks.

[0040] The following information entropy formula is used to calculate the information entropy of each image block after block, and the average value of the information entropy of all image blocks in the luminance component map is taken as the information entropy of the luminance component map.

[004...

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 processing method based on an adaptive PLIP model. The present invention first obtains the brightness component map of the image to be processed, and performs adaptive PLIP processing and detail processing on the brightness component map to obtain a detail enhancement map; inputs the brightness component map into the guide map filter to obtain the filter processing map; utilizes The exposure fusion method separately fuses the detail enhancement map, filter processing map, and brightness component map to obtain a fusion map; the fusion map is transformed into a space to obtain the result map. The invention can perform noise suppression, detail enhancement, edge preservation and other processing on natural images, and has the advantages of high detail accuracy and uniform brightness of the processing result image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an image enhancement method based on an adaptive logarithmic image processing PLIP model (Parameterized Logarithmic Image Processing) in the technical field of natural image processing. The invention can perform noise suppression, detail enhancement, edge preservation and other processing on low-illuminance images. Background technique [0002] Low-light images captured in the fields of remote sensing, military, industry, and medical technology have the problems of rich noise, blurred overall image details, and low average brightness of the image. The PLIP model can solve the problem that the pixel value exceeds the gray value interval caused by traditional operations on the image, but it cannot adaptively calculate the transformation parameters according to the characteristics of different regions of the image, which will lead to the loss of details. Therefore, t...

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 Patents(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20012G06T2207/20221G06T2207/20024G06T2207/20016G06T5/00
Inventor 王俊平张宏杰
Owner XIDIAN 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

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