A Novel Edge Detection Technique for Multi-Focus Images Using Image Fusion

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


Since last three decades, edge detection techniques have been drawing the attention of researchers due to its applications in 3D reconstruction, motion recognition, morphing, restoration, watermarking, image compression, and so on. Again, detecting edges in multi-focused images are one of the most challenging tasks. This paper deals with a novel edge detection approach for multi-focused images by means of complex wavelet-based image fusion. An illumination-invariant hyperbolic tangent filter (HBT) is applied followed by an adaptive thresholding to get the real edges. The shift invariance and directionally selective diagonal filtering as well as the ease of implementation of dual-tree complex wavelet transform (DT-CWT) ensure robust sub-band fusion. It helps in avoiding the ringing artifacts that are more pronounced in discrete wavelet transform (DWT). The fusion using DT-CWT also solves the problem of low contrast and blocking effects. To fulfill the symmetry of sub-sampling structure and bi-orthogonal property, a Q-shift dual-tree CWT has been implemented. In the adaptive thresholding technique, the threshold value varies smartly over the image. This helps to combat with a potent illumination gradient, shadowing, and multi-focus blurring of an image.


Adaptive thresholding DT-CWT DWT Edge detection HBT Image fusion Multi-focus image 


  1. 1.
    Frei, W., Chen, C.C.: Fast boundary detection: a generalization and a new algorithm. IEEE Trans. Comput. 26(10), 988–998 (1977)CrossRefGoogle Scholar
  2. 2.
    Marr, D., Hildreth, E.: Theory of edge detection. Proc. Royal Soc. Lond. B 207, 187–217 (1980)CrossRefGoogle Scholar
  3. 3.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)Google Scholar
  4. 4.
    Lacroix, V.: The primary raster: a multi resolution image description. In: Proceeding of 10th International Conference on Pattern Recognition, pp. 903–907 (1990)Google Scholar
  5. 5.
    Kovesi, P.: Phase congruency: a low level image invariant. Psychol. Res. 64, 136–148 (2000)CrossRefGoogle Scholar
  6. 6.
    Kumar, S., Ong, S.H., Ranganath, S., Chew, F.T.: A luminance and contrast-invariant edge-similarity measure. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2042–2048 (2006)CrossRefGoogle Scholar
  7. 7.
    Hill, P., Canagarajah, N., Bull, D.: Image fusion using complex wavelets. In: Proceedings of the 13th British Machine Vision Conference (BMVC-2002), pp. 487–496. Cardiff, UK (2002)Google Scholar
  8. 8.
    Akerman III, A.: Pyramid techniques for multisensor fusion, In: Proceedings of SPIE, vol. 1828, pp. 124–131. Boston, Massachusetts (1992)Google Scholar
  9. 9.
    Pajares, G., Cruz, J.: A wavelet-based image fusion tutorial. J. Pattern Recogn. Soc. (Elsevier) 37, 1855–1872 (2004)Google Scholar
  10. 10.
    Kingsbury, N.: Shift invariant properties of the dual-tree complex wavelet transform acoustics, speech, and signal processing. In: Proceeding of ICASSP 99, pp. 1221–1224 (1999)Google Scholar
  11. 11.
    Kingsbury, N.: A dual-tree complex wavelet transform with improved orthogonally and symmetry properties. In: International Conference on Image Processing (ICIP), vol. 2, pp. 375–378 (2000)Google Scholar
  12. 12.
    Ahmad, M.B., Choi, T.: Local threshold and boolean function based edge detection. IEEE Trans. Consum. Electron. 45, 674–679 (1999)CrossRefGoogle Scholar
  13. 13.
    Sun, W., Wang, K.: A multi-focus image fusion algorithm with DT-CWT. In: Proceedings of International Conference on Computational Intelligence and Security, pp. 147–151. IEEE Computer Society, Harbin, China (2007)Google Scholar
  14. 14.
    Chow, C.K., Kaneko, T.: Automatic boundary detection of the left ventricle from cineangiograms. Comp. Biomed. 5, 388–410 (1972)CrossRefGoogle Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringNational Institute of Technology RourkelaRourkelaIndia

Personalised recommendations