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

Self-adaptive image enhancement method

An image enhancement and adaptive technology, applied in image enhancement, image analysis, image data processing and other directions, can solve the problems of blurred edge features and detail information, low contrast, color distortion, etc. Detail information, the effect of avoiding color distortion

Pending Publication Date: 2020-11-20
NANCHANG UNIV
View PDF2 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In terms of improving image clarity, there are sparse representation and dictionary learning methods for noise removal, Smart Deblur restoration methods for motion blur removal, dark channel prior theory for haze removal, etc., but these methods have no effect on image edge features and Detailed information can bring blur effect
In terms of image edge feature extraction, there are differential methods such as Roberts, Canny, and Laplacian, but these differential methods will strengthen the influence of noise on the image
There are also a variety of image enhancement algorithms based on Retinex theory for correction of uneven illumination, but most of these algorithms will produce whitening and graying, color distortion and low contrast
The above image enhancement methods have certain limitations due to different application requirements, that is, different image enhancement methods are suitable for images with different characteristics

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 image enhancement method
  • Self-adaptive image enhancement method
  • Self-adaptive image enhancement method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0093] In order to verify the adaptive enhancement performance of the algorithm in this paper, different scene images collected in outdoor daytime, outdoor nighttime, and indoor daytime are selected for simulation experiments, and compared with the commonly used Contrast Limited AHE (CLAHE) method based on HSV The MSRCR algorithm (only the V component of the image is processed by the MSRCR algorithm in the HSV space, referred to as HSV-MSRCR) is compared, and evaluated by subjective visual effects and objective quality standards.

[0094] The parameters of the algorithm in this paper are set as follows: in the Otsu threshold method, the image stretch factor α=1.05, and the scale of the three Gaussian functions of the MSRCR algorithm is σ 1 =15, σ 2 =80, σ 3 = 250, color restoration parameters β = 0.75, γ = 6.5, the parameters of the comparison algorithm HSV-MSRCR and CLAHE are consistent with the parameters of the algorithm in this paper. The simulation results of different ...

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 the technical field of image enhancement, in particular to a self-adaptive image enhancement method, which comprises the following steps of S1, converting an original image tobe processed into an HSV color space from RGB, and decomposing the HSV color space into H, S and V components; s2, performing single-scale decomposition on the V component to obtain low-frequency component information and high-frequency component information of the V component of the image; s3, performing enhancement processing on the low-frequency component in the step S2, and then performing adaptive correction; s4, performing fuzzy enhancement on the high-frequency component in the step S2; s5, carrying out wavelet reconstruction on the low-frequency component and the high-frequency component after enhancement processing in the step S3 and the step S4 to obtain an enhanced brightness V component; s6, converting the HSV image back to the RGB color space; and S7, performing color restoration in the RGB space. According to the method, color distortion is avoided, the contrast and detail information of the image are improved, the visual effect of people is better met, and the method has self-adaptability.

Description

technical field [0001] The invention relates to the technical field of image enhancement, in particular to an adaptive image enhancement method. Background technique [0002] Image enhancement technology is a basic and very important technology in the field of image processing, and has been an unavoidable research topic in the field of image processing for a long time. How to properly enhance the image so that its features can be better protected while denoising the image, so as to improve the visual effect of the image and improve the clarity of the image is the problem to be solved in image enhancement. The traditional histogram equalization method is a relatively mature algorithm in the spatial domain, and its implementation is relatively simple. However, because this method will cause excessive image enhancement and cannot maintain the average brightness and entropy of the image, it is rarely used in actual engineering. For this reason, many improved histogram equalizat...

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): G06T5/00G06T7/90
CPCG06T7/90G06T2207/10024G06T5/90G06T5/70
Inventor 谢建宏王杰
Owner NANCHANG 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