Local Feature Image Fusion Algorithm Based on Wavelet Transform

  • Yuqiu Sun
  • Xiaoqiang Feng
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 124)

Abstract

An image fusion algorithm based on multi-scale wavelet transform according to image local features was put forward in this paper. Wavelet multi-scale decomposition was performed on original images and different wavelet coefficients could be obtained. Different fusion rules were applied to low-frequency and high-frequency coefficients. Local mean was computed in low-frequency area, which was taken as weigh to fuse low-frequency coefficients. And local information entropy was calculated in high-frequency region to fuse high-frequency coefficients. The fused image could be obtained by performing inverse wavelet transform. Standard deviation, average-gradient, entropy and mutual information were used as evaluation index to analyze the fused image. The experiment results show that the fused image had good clarity and contrast. The algorithm proposed in this paper was feasible.

Keywords

Mutual Information Original Image Image Fusion Wavelet Transform Fusion Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuqiu Sun
    • 1
  • Xiaoqiang Feng
    • 1
  1. 1.School of Information and MathematicsYangtze UniversityJingzhouChina

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