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

Sugandha Agarwal, O. P. Singh, Deepak Nagaria, Anil Kumar Tiwari and Shikha Singh
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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, India
Shikha Singh: Amity University Lucknow, Lucknow, India

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2017, vol. 8, issue 3, 42-54

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.

Date: 2017
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