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

Self-adaptive fractional order differential image enhancement algorithm

A fractional differentiation and image enhancement technology, applied in the field of image algorithms, can solve the problem of not being able to determine the optimal fractional value, and achieve the effect of ensuring the best effect

Inactive Publication Date: 2016-11-09
SHAANXI UNIV OF TECH
View PDF3 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] When using the existing method of combining wavelet and fractional differentiation to process images, the value of the sub-order number is still 0-1, and the optimal value of the sub-order number cannot be determined according to the characteristics of the image.

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 fractional order differential image enhancement algorithm
  • Self-adaptive fractional order differential image enhancement algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0025] refer to figure 1 ,Such as figure 1 An adaptive fractional differential image enhancement algorithm shown includes the following steps:

[0026] S1, calculate the image complexity according to the idea of ​​difference box dimension;

[0027] S2, calculating the number of sub-orders of the fractional differential according to the complexity of the image;

[0028] S3, performing wavelet transform on the image, decomposing the image into low frequency, high frequency in the horizontal direction, high frequency in the vertical direction, high frequency in the diagonal direction, and frequency...

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 adaptive fractional differential image enhancement algorithm, comprising the following steps: calculating the image complexity according to the idea of ​​difference box dimension; calculating the sub-order number of the fractional differential according to the image complexity; The first-order differential template processing enhances the extraction of high-frequency detail information, and the enhanced image retains low-frequency information; processes the high-frequency detail image in the horizontal direction; processes the high-frequency detail image in the vertical direction by wavelet decomposition; and processes the high-frequency detail image in the diagonal direction by wavelet decomposition processing; performing wavelet inverse transformation on the processed low-frequency, horizontal, vertical, and diagonal wavelet-decomposed images to obtain an enhanced image. The algorithm of the invention enhances and extracts the high-frequency information while retaining the low-frequency information of the image, and adaptively determines the algorithm sub-order parameter according to the complexity of the image, effectively ensuring the best effect of algorithm enhancement.

Description

technical field [0001] The invention relates to an image algorithm, in particular to an adaptive fractional differential image enhancement algorithm. Background technique [0002] Fractional differentiation is one of the branches of mathematical analysis. In recent years, many scholars have studied the application of this theory in image processing. The current general idea is to use the correlation between pixels and their adjacent pixels, and use multi-scale structure The improved template can be realized to improve the enhancement effect of image edge texture information, and the processing process is carried out in the air domain. [0003] The existing fractional order differential algorithms cannot give the best fractional order for image processing according to different image characteristics. These algorithms only verify that when the fractional order number is between 0-1, the use of fractional order differential algorithms can realize image processing. Enhancement,...

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): G06T5/00
CPCG06T5/00G06T2207/20004G06T2207/20064
Inventor 陈莉
Owner SHAANXI UNIV OF TECH
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