Comparative Analysis of Dwt, Reduced Wavelet Transform, Complex Wavelet Transform and Curvelet Transform |
Author(s): |
| Dhara Bhatt , S.P.B.PATEL INSTITUTE , MEHSANA; R.N.Patel, S.P.B.PATEL INSTITUTE , MEHSANA |
Keywords: |
| Image denoising, wavelet method, wavelet transform, Reduced Wavelet Transform, Comparative Analysis of DWT, Reduced Wavelet Transform, Complex Wavelet Transform, Curvelet Transform |
Abstract |
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Image denoising is the process to remove the noise from the image naturally corrupted by the noise. The wavelet method is one among various methods for recovering infinite dimensional objects like curves, densities, images, etc. The wavelet techniques are very effective to remove the noise because of their ability to capture the energy of a signal in few energy transform values. Though the wavelet transform have the best bases when it represents target functions which has dot singularity, it can hardly get the best bases when it present the singularity of line and hyper-plane. This makes the traditional two-dimensional wavelet transform in dealing with the image have some limitations. To overcome the above-mentioned shortcomings of Wavelet transform the theory of Curvelet transform was promoted. |
Other Details |
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Paper ID: IJSRDV2I9314 Published in: Volume : 2, Issue : 9 Publication Date: 01/12/2014 Page(s): 263-265 |
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