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

Color fusion image quality evaluation method based on vision task.

A color fusion and image technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as difficulty in measuring the comprehensive quality of color fusion images, and achieve the goal of being conducive to simplicity and accuracy, ensuring reliability, and being easy to quantify. Effect

Active Publication Date: 2012-09-12
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF0 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The objective evaluation indicators of image quality studied and proposed by predecessors, such as contrast, sharpness and color coordination, can reflect image quality attributes from different aspects, but it is difficult to measure the comprehensive quality of color fusion 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
  • Color fusion image quality evaluation method based on vision task.
  • Color fusion image quality evaluation method based on vision task.
  • Color fusion image quality evaluation method based on vision task.

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0100] The fused images of different scene types have different image characteristics, and the weight ratio of each evaluation index in explaining the perceived quality of the image changes. In order to make the image quality prediction model more targeted, the background of plants and urban buildings can be analyzed separately. The same regression analysis method as in Embodiment 1 is used for the three typical scene images of the sea and the sky background, respectively, to obtain a prediction model based on the image perception quality of the visual task. Only in the first step to obtain the visible light and infrared color fusion image of a typical scene, the image acquisition and score evaluation are only performed for a single background.

[0101] The regression models obtained by using the image of a single scene combined with the regression analysis method are:

[0102] a) Regression model of plant background fusion image

[0103] PQTD=0.768PCTB+0.246S-0.030, (R 2 =0...

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 typical scene color fusion image quality evaluation method based on a vision task and belongs to the image fusion technology field in image processing. According to the invention, through a subjective evaluation experiment, a regression analysis method is used to establish a fusion image integration quality prediction model based on the vision task. Object background perception contrast and image definition can be used to effectively predict an image perception quality based on object detection. Color compatibility and the definition are used to effectively predict the image perception quality based on scene understanding. Compared to the traditional image quality evaluation method, an image quality evaluation index based on the vision task can carry out comprehensive evaluation of the image quality aiming at an application purpose of the color fusion image. Although it is difficult to perform objective quantification, three basic indexes of the object background contrast, definition and the compatibility comprised in a prediction model are easy to carry out quantification calculating. An effective solution is provided for a problem of the fusion image integration quality objectivity evaluation.

Description

technical field [0001] The invention relates to a visual task-based color fusion image quality evaluation method, which belongs to the technical field of color fusion in image processing. Background technique [0002] In recent years, with the development of multi-band image sensor technology, the research of multi-band image fusion algorithm has been paid more attention by people. Among them, the color (night vision) image fusion method of visible light and infrared can make full use of the color vision characteristics of human eyes, which can effectively improve the visual field. The photoelectric imaging system has the ability to detect and recognize objects in the scene, reduce the false alarm rate and recognition error, and shows a wide range of application prospects in situational awareness and target detection, and practical systems and equipment have been successfully applied. At the same time, how to evaluate the fusion effect, that is, how to evaluate the quality o...

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): G06T7/00G06T7/40
Inventor 金伟其高绍姝王岭雪王霞骆媛路陆
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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