Image Enhancement by Unsharp Mask Filtering Based on Detrending Method

  • Authors

    • Jeong-Hwan Kim
    • Kang-Hwi Lee
    • Jeong-Whan Lee
    • Kyeong-Seop Kim
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.23693
  • Unsharp Mask (UM). Heart Rate Variability (HRV), Zigzag Scanning, Trend

  • Abstract

    Background/Objectives: Unsharp Masking (UM) technique has been widely used to enhance high-frequency details such as edges by subtracting its local blurriness involved in pre-fixed low-pass filter mask operations and adding high-frequency weighting elements to  original image. However, UM process has a major drawback: it estimates only local blurriness by performing convolution operation involved with the pixels in the limited spatial scope. With this aim, we present a new UM method by detrending analysis where overall blurriness in a given image is estimated in terms of a slow and non-stationary global tendency that is resultant of merging adjacent local trends.

    Methods/Statistical analysis: In our study, global non-stationary trend was estimated by applying detrending method that was originally developed based on smoothness priors approach to estimate slow and non-stationary trend in Heart Rate Variability (HRV) analysis. In our study, non-stationary trend was resolved by merging subsequent local trends due to the limitations in inverse-matrix computations and this global tendency was interpreted as non-stationary part for applying detrending analysis.

    Findings: Our test results reveal that the suggested UM approach can efficiently estimate the global trend of an image and subsequently it can be utilized to improve the sharpness and contrast of an image.

    Improvements/Applications: In this study, zigzag-scanning algorithm was used to convert two-dimensional image data into one-dimensional vector form to estimate non-stationary trend of an image based on detrending analysis. In the future study, it might need to explore the role of specific scanning-order how this factor affects the performance of estimating local blurriness of an image.

     

  • References

    1. [1] Polesel, A., ramponi, G., & Mathews, V. J. (2000). Image enhancement via adaptive unsharp masking, IEEE Transactions on Image Processing, 9(3), 505-510.

      [2] Ilk, H. G., Jane, O., & Ilk, O. (2011). The effect of Laplacian filter in adaptive unsharp masking for infrared image enhancement. Infrared Physics & Technology, 54, 427-438.

      [3] Luft, T., Colditz, C., & Deussen, O. (2006). Image enhancement by unsharp masking the depth buffer. ACM Transactions on Graphics (TOG) – Proceedings of ACM SIGGRAPH2006, 25(3), 1206-1213.

      [4] Panetta, K., Zhou, Y., Agaian, S., &Jia, H. (2011). Nonlinear unsharp masking for mammogram enhancement. IEEE Transctions on Information Technology in Biomedicine, 15(6).

      [5] Kim, D. H., & Ye S. Y. (2014). CAD for detection of brain tumor using the symmetry contribution from MR image applying unsharp mask filter. Transactions on Electrical and Electronic Materials, 45(4), 230-234.

      [6] Nasonova, A. A., &Krylov, A. S. (2014). Determination of image edge width by unsharp masking. Computational Mathematics and Modeling, 25(1), 76-82.

      [7] Sikai, Z., & Sheng, C. (2016). An improved unsharp masking model for intensive care unit chest radiograph enhancement. 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD).

      [8] Tarvainen, M. P., Perttu, O., Ranta-aho, &Karjalainen, P. A. (2002). An advanced detrending method with application to HRV analysis. IEEE Transactions on Biomedical Engineering, 49(2), 172-175.

      [9] Mulla, A., Baviskar, J., Baviskar, A., & Warty C. (2014). Image compression scheme based on zig-zag 3D-DCT and LDPC coding. 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 24-27.

      [10] Pei, S. C., Ding, J. J., & Lee, T. H. H. (2010). Two-dimensional orthogonal DCT expansions in triangular and trapezoid regions. Proc. SPIE 7744, Visual Communications and Image Processing.

      [11] Shin, S. W., Kim, K. S., Song, C. G., Lee, J. W., Kim, J. H., &Jeung, G. W. (2015). Removal of baseline wandering in ECG signal by improved detrending method. Bio-Medical Materials and Engineering, 26, S1087-S1093.

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  • How to Cite

    Kim, J.-H., Lee, K.-H., Lee, J.-W., & Kim, K.-S. (2018). Image Enhancement by Unsharp Mask Filtering Based on Detrending Method. International Journal of Engineering & Technology, 7(4.39), 26-29. https://doi.org/10.14419/ijet.v7i4.39.23693

    Received date: 2018-12-11

    Accepted date: 2018-12-11

    Published date: 2018-12-13