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Image Quality Improvement Using Shift Variant and Shift Invariant Based Wavelet Transform Methods: A Novel Approach

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  • Sugandha Agarwal

    (Amity University Lucknow, Lucknow, India)

  • O. P. Singh

    (Amity University Lucknow, Lucknow, India)

  • Deepak Nagaria

    (Bundelkhand Institute of Engineering and Technology, Jhansi, India)

  • Anil Kumar Tiwari

    (Amity University Lucknow, Lucknow, India)

  • Shikha Singh

    (Amity University Lucknow, Lucknow, India)

Abstract

The concept of Multi-Scale Transform (MST) based image de-noising methods is incorporated in this paper. The shortcomings of Fourier transform based methods have been improved using multi-scale transform, which help in providing the local information of non-stationary image at different scales which is indispensable for de-noising. Multi-scale transform based image de-noising methods comprises of Discrete Wavelet Transform (DWT), and Stationary Wavelet Transform (SWT). Both DWT and SWT techniques are incorporated for the de-noising of standard images. Further, the performance comparison has been noted by using well defined metrics, such as, Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR) and Computation Time (CT). The result shows that SWT technique gives better performance as compared to DWT based de-noising technique in terms of both analytical and visual evaluation.

Suggested Citation

  • Sugandha Agarwal & O. P. Singh & Deepak Nagaria & Anil Kumar Tiwari & Shikha Singh, 2017. "Image Quality Improvement Using Shift Variant and Shift Invariant Based Wavelet Transform Methods: A Novel Approach," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 8(3), pages 42-54, July.
    • Handle: RePEc:igg:jmdem0:v:8:y:2017:i:3:p:42-54
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