Image Denoising using DWT-EEMD Algorithm |
Author(s): |
| Bela , Galaxy Global Group of institute ; Ankita Mittal, Galaxy Global Group of institute |
Keywords: |
| Wavelet transform, inverse transform, thresholding, denoise |
Abstract |
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The massive amount of data required for images is a primary reason for the development of many sub areas within the field of computer imaging such as image segmentation and compression. Whatever may be the way of transmission, the data tends to get noisy and thereby the further processing does not lead to good results. Hence, it is very essential to keep the data close to originality. In order to achieve this in terms of the concerned work, wavelet transforms have been applied: Discrete wavelet transform and EEMD. In this thesis, a new technique which is combination of Enhanced Empirical Mode Decomposition (EEMD), has been presented along with the standard wavelet thresholding techniques like hard thresholding to denoise the image. |
Other Details |
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Paper ID: IJSRDV2I6045 Published in: Volume : 2, Issue : 6 Publication Date: 01/09/2014 Page(s): 42-45 |
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