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

No-reference image quality evaluation method based on multifractal spectrum

A multi-fractal spectrum, reference image technology, applied in the field of digital image quality evaluation

Inactive Publication Date: 2014-09-10
ZHEJIANG UNIV
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to address the inadequacies of the traditional single fractal-based image objective quality evaluation method in terms of measurement intuition and accuracy, fully considering that multiple (even infinite) parameters contained in the multi-fractal spectrum can completely describe the image. The complex fractal details contained in the multi-fractal spectrum provide a full-reference image quality objective evaluation method based on multi-fractal spectrum

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
  • No-reference image quality evaluation method based on multifractal spectrum
  • No-reference image quality evaluation method based on multifractal spectrum
  • No-reference image quality evaluation method based on multifractal spectrum

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] Step (1): Input the reference image R, such as figure 1 Shown are images of bikes in the LIVE database;

[0057] Step (2): Perform grayscale processing on the reference image R. When the reference image R has a border, cut out the border, according to figure 1 As shown, it can be seen that it has a gray border, and 5 pixels can be removed from the top, bottom, left, and right sides, such as figure 2 shown;

[0058] Step (3): The length and width of the image processed in step (2) are cropped so that its pixels become an integer multiple of 64, and divided into image fragments with a size of 64×64 pixels, such as image 3 shown;

[0059] Step (4): Build a multifractal spectrum for each image fragment, such as from image 3 Extract the image in the upper left corner such as Figure 4 , to establish a multifractal spectrum;

[0060] The establishment steps of the multifractal spectrum are as follows:

[0061] 1) Since the grayscale of the 8-bit bmp format image sto...

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 a no-reference image quality evaluation method based on a multifractal spectrum, and belongs to the field of image processing. Themethod of the specific embodimentcomprises the following steps: (1) inputting a distorted image, carrying out grey processing to the image, and removing a border; (2) clipping the length and the width of the image to cause the length and the width of the image to be the integral multiple of 64, and segmenting the image into a plurality of image fragments of 64*64 pixel; (3) establishing a database of the distortedimages of the same type, and training multifractal spectrum reference data from the distorted image database; (4) inputting the distorted image to obtain the reference data of the multifractal spectrums aq and fq of the distorted image; and (5) solving distances among the corresponding points of the multifractal spectrums in the database. According to the no-reference image quality evaluation method based on the multifractal spectrum, the multifractal spectrum is established to extract image characteristics, image quality evaluation is carried out on the basis of data training, and an evaluation result conforms to the subjective cognizance of human vision.

Description

technical field [0001] The invention belongs to the technical field of digital image quality evaluation, and relates to an objective evaluation method of image quality based on multi-fractal spectrum without reference. Background technique [0002] There are two categories of image quality assessment methods. 1) Subjective evaluation method. Image quality was rated by observers. People are the final users of images, and subjective quality evaluation is the most accurate and reliable image quality evaluation method. However, because it is time-consuming, expensive, and easily affected by factors such as the experimental environment, the observer's knowledge level, and preferences, the evaluation results are often unstable, and it is not suitable for real-time systems. 2) Objective evaluation method. With the advantages of simplicity, real-time, repeatability and easy integration, etc., it has developed rapidly in recent decades and has become a research hotspot in the ima...

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): G06T7/00
Inventor 丁勇贾孟晗叶葳黄汝霖张航
Owner ZHEJIANG 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