Image Denoising Using Wavelet Transform and Wavelet Transform with Enhanced Diversity
| Autor: | Smriti Bhatnagar, Vaibhav Nigam, Sajal Luthra |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Discrete wavelet transform
Lifting scheme business.industry Second-generation wavelet transform Stationary wavelet transform ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION General Engineering Wavelet transform Pattern recognition Data_CODINGANDINFORMATIONTHEORY Wavelet packet decomposition Wavelet Computer Science::Computer Vision and Pattern Recognition Artificial intelligence Harmonic wavelet transform business Mathematics |
| Zdroj: | Advanced Materials Research. :866-870 |
| ISSN: | 1662-8985 |
| DOI: | 10.4028/www.scientific.net/amr.403-408.866 |
| Popis: | This paper is a comparative study of image denoising using previously known wavelet transform and new type of wavelet transform, namely, Diversity enhanced discrete wavelet transform. The Discrete Wavelet Transform (DWT) has two parameters: the mother wavelet and the number of iterations. For every noisy image, there is a best pair of parameters for which we get maximum output Peak Signal to Noise Ratio, PSNR. As the denoising algorithms are sensitive to the parameters of the wavelet transform used, in this paper comparison of DEDWT to DWT has been presented. The diversity is enhanced by computing wavelet transforms with different parameters. After the filtering of each detail coefficient, the corresponding wavelet transforms are inverted and the estimated image, having a higher PSNR, is extracted. To benchmark against the best possible denoising method three thresholding techniques have been compared. In this paper we have presented a more practical, implementation oriented work. |
| Databáze: | OpenAIRE |
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