Infrared Image Enhancement Algorithm based on Weighted Guided Filtering

Jiawei Luo, Yanmei Zhang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Aiming at the problems of blurred details and over enhancement in traditional infrared image enhancement algorithms, an infrared image enhancement method based on guided weighted image filtering is proposed. Firstly, the gradient difference between the pixels around the image is used to find the isolated noise and the median filter is used to filter it; Then, the weighted guided image filter is used to decompose the image to obtain the basic component and detail component. The Contrast Limited Adaptive Histogram Equalization (CLAHE) is used to equalize the stretched contrast in the basic layer, and the nonlinear function is used to enhance and suppress the noise in the detail layer; Finally, different levels of results are fused to obtain contrast and detail enhanced infrared images. This method is used to simulate many groups of infrared images of different scenes, and compared with many enhancement methods. The results show that the proposed method has better results in infrared image detail and contrast enhancement.

Original languageEnglish
Title of host publicationProceedings of 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages332-336
Number of pages5
ISBN (Electronic)9781665428767
DOIs
Publication statusPublished - 2021
Event2nd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021 - Chongqing, China
Duration: 17 Dec 202119 Dec 2021

Publication series

NameProceedings of 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021

Conference

Conference2nd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021
Country/TerritoryChina
CityChongqing
Period17/12/2119/12/21

Keywords

  • CLAHE
  • image enhancement
  • infrared image
  • nonlinear function
  • weighted guided image filter

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