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All in focus fusion using guided filter

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Abstract

A guided filter based fusion scheme for multi focus images is proposed. The source images are decomposed into base and detail layers. The base layers contain the large scale variations and are averaged out to obtain the base layer of the fused image. The weights of detail layers are computed based on whether the objects in a particular image is in focus compared to the same object in all other images. Guided filtering is performed to further refine the weights. Simulation results reveal the significance of proposed scheme.

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References

  • Burt, P. J., & Kolezynski, R. J. (1993). Enhanced image capture through fusion. In International Conference on Computer Vision (pp. 173–182). Berlin, Germany.

  • Choi, M., Kim, R., & Kim, M. (2004). The curvelet transform for image fusion. International Society for Photogrammetry and Remote Sensing, 35, 59–64.

    Google Scholar 

  • De, I., Chanda, B., & Chattopadhyay, B. (2006). Enhancing effective depth-of-field by image fusion using mathematical morphology. Image and Vision Computing, 24(12), 1278–1287.

    Article  Google Scholar 

  • De, I., & Chanda, B. (2013). Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure. Information Fusion, 14(2), 136–146.

    Article  Google Scholar 

  • Doa, M. N., & Vetterli, M. (2005). The contourlet transform: An efficient directional multiresolution image representation. IEEE Transactions on Image Processing, 14(12), 2091–2106.

    Article  Google Scholar 

  • Geng, P., Gao, Z., & Hu, C. (2013). Multi-focus Image Fusion using the local neighbor num of laplacian in NSCT domain. International Journal of Signal Processing, Image Processing and Pattern Recognition, 6(4), 69–80.

    Google Scholar 

  • He, K., Sun, J., & Tang, X. (2013). Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1397–1409.

    Article  Google Scholar 

  • Helicon Soft, Helicon Focus. (2011). http://www.heliconsoft.com/heliconfocus.html

  • Jameel, A., Ghafoor, A., & Riaz, M. M. (2014). Improved guided image fusion for magnetic resonance and computed tomography imaging. The Scientfic World Journal, 2014, 1–7.

  • Li, S., & Yang, B. (2008). Multifocus image fusion by combining curvelet and wavelet transform. Pattern Recognition Letters, 29(9), 1295–1301.

    Article  Google Scholar 

  • Li, H., Chai, Y., & Li, Z. (2013). Multi-focus image fusion based on nonsubsampled contourlet transform and focused regions detection. Optik-International Journal for Light and Electron Optics, 124(1), 40–51.

    Article  Google Scholar 

  • Liu, Y., Jin, J., Wang, Q., Shen, Y., & Dong, X. (2014). Region level based multi-focus image fusion using quaternion wavelet and normalized cut. Signal Processing, 97, 9–30.

    Article  Google Scholar 

  • Malik, A. S., & Choi, T. S. (2007). Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery. Pattern Recognition, 40(1), 154–170.

    Article  MATH  Google Scholar 

  • Pertuz, S., Puig, D., Garcia, M., & Fusiello, A. (2013). Generation of all-in-focus images by noise-robust selective fusion of limited depth-of-field images. IEEE Transactions on Image Processing, 22(3), 1242–1251.

    Article  MathSciNet  Google Scholar 

  • Sun, Y., Duthaler, S., & Nelson, B. (2004). Autofocusing in computer microscopy: Selecting the optimal focus algorithm. Microscopy Research and Technique, 65(3), 139–149.

    Article  Google Scholar 

  • Wan, T., Zhu, C., & Qin, Z. (2013). Multifocus image fusion based on robust principal component analysis. Pattern Recognition Letters, 34(9), 1001–1008.

    Article  Google Scholar 

  • Wang, Z., & Bovik, A. (2002). A universal image quality index. IEEE Signal Processing Letters, 9(3), 81–84.

    Article  Google Scholar 

  • Wang, N., Wang, W., & Guo, X. (2014). Multisource image fusion based on DWT and simplified pulse coupled neural network. Applied Mechanics and Materials, 457, 736–740.

    Article  Google Scholar 

  • Wang, N., Ma, Y., & Wang, W. (2014). DWT-based multisource image fusion using spatial frequency and simplified pulse coupled neural network. Journal of Multimedia, 9(1), 159–165.

    Google Scholar 

  • Yang, X., Yang, W., & Pei, J. (2000). Different focus points images fusion based on wavelet decomposition. In International Conference on Information Fusion (Vol. 1, pp. 3–8). Paris, France.

  • Zerene Systems. (2011). Zerene Stacker, Richland, WA. http://www.zerenesystems.com/cms/stacker

  • Zhang, B., Zhang, C., Yuanyuan, L., Jianshuai, W., & He, L. (2014). Multi-focus image fusion algorithm based on compound PCNN in surfacelet domain. Optik-International Journal for Light and Electron Optics, 125(1), 296–300.

    Article  Google Scholar 

  • Zhou, Z., Li, S., & Wang, B. (2014). Multi-scale weighted gradient-based fusion for multi-focus images. Information Fusion. doi:10.1016/j.inffus.2013.11.005.

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Authors and Affiliations

  1. Military College of Signals, National University of Sciences and Technology (NUST), Islamabad, Pakistan

    Amina Jameel & Abdul Ghafoor

  2. Centre for Advanced Studies in Telecommunication (CAST), COMSATS, Islamabad, Pakistan

    Muhammad Mohsin Riaz

Authors
  1. Amina Jameel
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  2. Abdul Ghafoor
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  3. Muhammad Mohsin Riaz
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Corresponding author

Correspondence to Abdul Ghafoor.

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Jameel, A., Ghafoor, A. & Riaz, M.M. All in focus fusion using guided filter. Multidim Syst Sign Process 26, 879–889 (2015). https://doi.org/10.1007/s11045-014-0302-7

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  • DOI: https://doi.org/10.1007/s11045-014-0302-7

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