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Image Filtering Enhancement

  • Zhen Guo
  • Hang Pan
  • Jinlong Chen
  • Xianjun ChenEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10942)

Abstract

With the development of science and technology, mankind has entered the information age. Image has become the main source of human access to information. However, in the actual process of image signal transmission, the loss and damage of data packet are inevitable due to the physical defects of the channel, which lead to a serious decline in the quality of the video stream. So it is necessary and even urgent now to do some research work on image enhancement technology. In this paper, the image enhancement algorithms that are commonly used, such as bilateral filtering algorithm, homomorphic filtering algorithm, are analyzed in image processing. In the design of the image enhancement, the best modeling and design schemes are chosen according to the comparison. The experimental results demonstrate that the bilateral filtering algorithm can effectively maintain the details of the image edges and make the image more smooth; the homomorphic filtering algorithm can effectively adjust the image gray range, so that the image details on the image area can be increased, and the algorithm can handle the image with inhomogeneous intensity. This work will lay a good foundation of further research.

Keywords

Image enhancement Homomorphic filtering Bilateral filtering 

Notes

Acknowledgments

This research work is supported by the grant of Guangxi science and technology development project (No: AC16380124), the grant of Guangxi Science Foundation (No:2017GXNSFAA198226),the grant of Guangxi Key Laboratory of Cryptography & Information Security of Guilin University of Electronic Technology (No: GCIS201604), the grant of Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics of Guilin University of Electronic Technology (No:GIIP201602), and the grant of Innovation Project of GUET Graduate Education (2017YJCX55).Guangxi Key Laboratory of Trusted Software (No kx201601), Guangxi Cooperative Innovation Center of cloud computing and Big Data, Guangxi Colleges and Universities Key Laboratory of cloud computing and complex systems (No YD16E11), Guangxi Key Laboratory of cryptography and information security (GCIS201601, GCIS201602, GCIS201603).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Zhen Guo
    • 1
    • 2
  • Hang Pan
    • 1
  • Jinlong Chen
    • 2
  • Xianjun Chen
    • 1
    • 3
    Email author
  1. 1.Guangxi Key Laboratory of Cryptography and Information SecurityGuilin University of Electronic TechnologyGuilinChina
  2. 2.Key Laboratory of Intelligent Processing of Computer Image and GraphicsGuilin University of Electronic TechnologyGuilinChina
  3. 3.Information Engineering SchoolHaikou College of EconomicsHaikouChina

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