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Circuits, Systems, and Signal Processing

, Volume 38, Issue 12, pp 5576–5605 | Cite as

Multi-scale Guided Image and Video Fusion: A Fast and Efficient Approach

  • Durga Prasad Bavirisetti
  • Gang XiaoEmail author
  • Junhao Zhao
  • Ravindra Dhuli
  • Gang Liu
Article
  • 126 Downloads

Abstract

In this paper, we propose a general purpose, simple and fast fusion algorithm based on guided image filter. The proposed method can well combine useful source image information into the fused image supported by multi-scale image decomposition, structure transferring property, visual saliency detection, and weight map construction. Multi-scale image decomposition is appropriate to represent and manipulate image features at various scales. Structure transferring property enabled by our algorithm can induce structures of one source image into the other. A new visual saliency detection based on guided image filter introduced in this paper is able to extract significant regions from visually different images of the same scene. The choice of weight maps helped to integrate the complementary information pixel by pixel at each scale. Experimental outcomes of the proposed method are compared and analyzed with traditional and recent guided image filter-based fusion algorithms in terms of visual quality, fusion metrics and run time. In addition, to enhance fusion results further we made an effort to find a suitable image and video enhancement algorithm. The fusion performance analysis clearly indicates that the proposed method is very promising along with less run time.

Keywords

Edge preserving Guided image filter Image fusion Multi-scale image decomposition Structure transferring Visual saliency 

Notes

Acknowledgments

This work is sponsored by National Program on Key Basic Research Project (2014CB744903), National Natural Science Foundation of China (61673270), Shanghai Pujiang Program(16PJD028), Shanghai Industrial Strengthening Project (GYQJ-2017-5-08), Shanghai Science and Technology Committee Research Project (17DZ1204304) and Shanghai Engineering Research Center of Civil Aircraft Flight Testing. We would like to thank our postdoctoral researcher Dr. Xingchen Zhang for English proof reading of the manuscript.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Durga Prasad Bavirisetti
    • 1
  • Gang Xiao
    • 1
    Email author
  • Junhao Zhao
    • 1
  • Ravindra Dhuli
    • 2
  • Gang Liu
    • 3
  1. 1.School of Aeronautics and AstronauticsShanghai Jiao Tong UniversityShanghaiChina
  2. 2.School of Electronics EngineeringVIT UniversityAmaravatiIndia
  3. 3.School of Automation EngineeringShanghai University of Electrical PowerShanghaiChina

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