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A wavelet transform based contrast enhancement method for underwater acoustic images

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Abstract

Dredging the surface of the ocean to identify both living and non living things nowadays has become an unproblematic task with the help of the acoustic instruments. Side scan sonar is one of such instruments used for far-reaching the seafloor. The sonar captures the scene of the sea bed by releasing fan shaped sound signal which is then converted to images. These images are normally gray scale low contrast images where the objects cannot be viewed clearly. The proposed method uses the Stationary Wavelet Transform (SWT) to decompose the input image into four components such as Low–Low, Low–High, High–Low and High–High components. The low frequency component is sharpened using Laplacian filter and a mask is created by subtracting the LL component with the filtered image. Then the enhanced LL component is obtained by adding the mask to the input image. The high contrast image is reconstructed by applying inverse stationary wavelet transform which combines the enhanced LL component and the other sub-bands. The results have been compared by replacing the SWT with the Discrete Wavelet Transform by interpolating the frequency components. The quantitative and visual results show that the proposed method using SWT outperforms the state of art techniques in terms of contrast.

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References

  • Arici, T., Dikbas, S., & Altunbasak, Y. (2009). A histogram modification framework and its application for image contrast enhancement. IEEE Transactions on Image Processing, 18(9), 1921–1935.

    Article  MathSciNet  MATH  Google Scholar 

  • Bhandari, A. K., Kumar, A., Chaudhary, S., & Singh, G. K. (2017). A new beta differential evolution algorithm for edge preserved colored satellite image enhancement. Multidimensional Systems and Signal Processing, 28(2), 495–527.

    Article  MATH  Google Scholar 

  • Chen, Z. Y., Abidi, B. R., Page, D. L., & Abidi, M. A. (2006a). Gray-level grouping (GLG): An automatic method for optimized image contrast enhancement-part I: The basic method. IEEE Transactions on Image Processing, 15(8), 2290–2302.

    Article  Google Scholar 

  • Chen, Z. Y., Abidi, B. R., Page, D. L., & Abidi, M. A. (2006b). Gray-level grouping (GLG): An automatic method for optimized image contrast enhancement-part II: The variations. IEEE Transactions on Image Processing, 15(8), 2303–2314.

    Article  Google Scholar 

  • Cherifi, D., Beghdadi, A., & Belbachir, A. H. (2010). Color contrast enhancement method using steerable pyramid transform. Signal, Image and Video Processing, 4(2), 247–262. https://doi.org/10.1007/s11760-009-0115-6.

    Article  MATH  Google Scholar 

  • Chouhan, R., Pradeep Kumar, C., Kumar, R., & Jha, R. K. (2012). Contrast enhancement of dark images using stochastic resonance in wavelet domain. International Journal of Machine Learning and Computing, 2(5), 711. https://doi.org/10.7763/IJMLC.2012.V2.220.

    Article  Google Scholar 

  • Demirel, H., Ozcinar, C., & Anbarjafari, G. (2010). Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition. IEEE Geoscience and Remote Sensing Letters, 7(2), 333–337.

    Article  Google Scholar 

  • Dura, E. (2011). Image processing techniques for the detection and classification of man made objects in side-scan sonar images. Chennai: INTECH Open Access Publisher.

    Book  Google Scholar 

  • Gonzalez, R. C., & Woods, R. E. (2007). Digital image processing. Upper Saddle River: Prentice-Hall.

    Google Scholar 

  • Gupta, B., & Tiwari, M. (2016). A tool supported approach for brightness preserving contrast enhancement and mass segmentation of mammogram images using histogram modified grey relational analysis. Multidimensional Systems and Signal Processing, 28(4), 1549–1567.

  • Liu, J., Zhou, C., Chen, P., & Kang, C. (2017). An efficient contrast enhancement method for remote sensing images. IEEE Geoscience and Remote Sensing Letters, 14(10), 1715–1719.

    Article  Google Scholar 

  • Maragatham, G., & Md Mansoor Roomi., S. (2016). PSO-based stochastic resonance for automatic contrast enhancement of images. Signal, Image and Video Processing, 10(1), 207–214. https://doi.org/10.1007/s11760-014-0728-2.

    Article  Google Scholar 

  • Murino, V., & Trucco, A. (2000). Three-dimensional image generation and processing in underwater acoustic vision. Proceedings of the IEEE, 88(12), 1903–1948.

    Article  Google Scholar 

  • Ooi, C. H., & Isa, N. A. M. (2010). Quadrants dynamic histogram equalization for contrast enhancement. IEEE Transactions on Consumer Electronics, 56, 4.

    Google Scholar 

  • Priyadharsini, R., Sree Sharmila, T., & Rajendran, V. (2015). Underwater image enhancement using discrete wavelet and KL transform. In Proceedings of IEEE international conference on applied and theoretical computing and communication technology, Karnataka, India, pp. 563–567.

  • Priyadharsini, R., Sree Sharmila, T., & Rajendran, V. (2017). Acoustic image enhancement using Gaussian and laplacian pyramid–A multiresolution based technique. Multimedia Tools and Applications, 76, 1–15. https://doi.org/10.1007/s11042-017-4466-7.

    Article  Google Scholar 

  • Sheet, D., Garud, H., Suveer, A., Mahadevappa, M., & Chatterjee, J. (2010). Brightness preserving dynamic fuzzy histogram equalization. IEEE Transactions on Consumer Electronics, 56(4), 2475–2480.

    Article  Google Scholar 

  • Singh, S. R. (2014). Enhancement of contrast and resolution of gray scale and color images by wavelet decomposition and histogram shaping and shifting. In International conference on medical imaging, m-health and emerging communication systems (MedCom) (pp. 300–305). IEEE.

  • Sree Sharmila, T., Kadarkarai, R., & Thangaswamy, S. R. R. (2013a). Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy. Journal of Electronic Imaging. https://doi.org/10.1117/1.JEI.22.1.013013.

  • Sree Sharmila, T., Kadarkarai, R., & Thangaswamy, S. R. R. (2013b). Impact of applying preprocessing techniques for improving classification accuracy. Signal Image and Video Processing, 8(1), 149–157. https://doi.org/10.1007/s11760-013-0505-7.

    Article  Google Scholar 

  • SreeSharmila, T., & Kadarkarai, R. (2014). Efficient analysis of hybrid directional lifting technique for satellite image denoising. Signal, Image and Video Processing, 8(7), 1399–1404. https://doi.org/10.1007/s11760-012-0369-2.

    Article  Google Scholar 

  • Suresh, S., Lal, S., Reddy, C. S., & Kiran, M. S. (2017). A novel adaptive cuckoo search algorithm for contrast enhancement of satellite images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(8), 3665–3676.

  • Zhou, Y., Li, Q., & Huo, G. (2015). Automatic side-scan sonar image enhancement in curvelet transform domain. Mathematical Problems in Engineering. https://doi.org/10.1155/2015/493142.

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Acknowledgements

We would like to thank SSN Institutions for providing financial support to carry out this work successfully. We would also like to thank Mr. Pankaj Tiwari, System Engineer, Unique Hydrographic Systems Pvt. Ltd for helping us in collecting the images.

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Correspondence to R. Priyadharsini.

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Priyadharsini, R., Sree Sharmila, T. & Rajendran, V. A wavelet transform based contrast enhancement method for underwater acoustic images. Multidim Syst Sign Process 29, 1845–1859 (2018). https://doi.org/10.1007/s11045-017-0533-5

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  • DOI: https://doi.org/10.1007/s11045-017-0533-5

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