Infrared and visual image fusion method based on discrete cosine transform and local spatial frequency in discrete stationary wavelet transform domain

Xin Jin, Qian Jiang, Shaowen Yao*, Dongming Zhou, Rencan Nie, Sj Lee, Kangjian He

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

In order to promote the performance of infrared and visual image fusion and provide better visual effects, this paper proposes a hybrid fusion method for infrared and visual image by the combination of discrete stationary wavelet transform (DSWT), discrete cosine transform (DCT) and local spatial frequency (LSF). The proposed method has three key processing steps. Firstly, DSWT is employed to decompose the important features of the source image into a series of sub-images with different levels and spatial frequencies. Secondly, DCT is used to separate the significant details of the sub-images according to the energy of different frequencies. Thirdly, LSF is applied to enhance the regional features of DCT coefficients, and it can be helpful and useful for image feature extraction. Some frequently-used image fusion methods and evaluation metrics are employed to evaluate the validity of the proposed method. The experiments indicate that the proposed method can achieve good fusion effect, and it is more efficient than other conventional image fusion methods.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalInfrared Physics and Technology
Volume88
DOIs
StatePublished - 1 Jan 2018

Keywords

  • Discrete cosine transform
  • Discrete stationary wavelet transform
  • Infrared and visual image fusion
  • Spatial frequency

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