Feature Enhancement Derivative Fusion Algorithm Based on Luminance Evaluation Technology
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Focused on the low-light images obtained from dynamic range, illumination condition, image acquisition equipment, etc., a feature enhancement derivative fusion algorithm based on luminance evaluation technology was proposed to achieve contrast adjustment and feature enhancement of the low-light images. Firstly, the brightness evaluation technique was used to optimize the brightness of the low-light image to obtain the exposure ratio map. Then, combining exposure ratio map and improved chi-square distribution function model, two derivatives with enhanced features were obtained for fusion. Finally, the fusion image was obtained by using the improved derivative fusion algorithm. The experimental results indicate that the proposed algorithm achieves the better results including brightness order error, visual information fidelity and image mutual information, improves the image contrast while preserving the well-exposed region, and it can recover the edge and texture details of the low-luminance region.

    Reference
    Related
    Cited by
Get Citation

韦超,唐丽娟,陈冠楠.基于亮度评估技术的特征增强衍生图融合算法.计算机系统应用,2019,28(11):195-201

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 19,2019
  • Revised:May 16,2019
  • Adopted:
  • Online: November 08,2019
  • Published: November 15,2019
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063