A COMPARATIVE STUDY ON WAVELET BASED IMAGE DENOISING
| Autor: | Nisha Joy, T. John |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Discrete wavelet transform
business.industry Computer science Noise reduction Gabor wavelet MathematicsofComputing_NUMERICALANALYSIS ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Wavelet transform Image processing Pattern recognition Data_CODINGANDINFORMATIONTHEORY Non-local means Wavelet Computer Science::Computer Vision and Pattern Recognition Video denoising Computer vision Artificial intelligence business |
| Zdroj: | International Journal of Research in Engineering and Technology. :257-260 |
| ISSN: | 2319-1163 2321-7308 |
| DOI: | 10.15623/ijret.2016.0516055 |
| Popis: | The field of image processing deals with a major issue, i.e., the suppression of noise from the wanted images. The intention of this message is to highlight some of the unique properties of spline wavelets. In this paper image denoising is performed using simulated noise images with various characteristics with the help of semi-orthogonal spline wavelets in comparison with CDF 9/7 wavelets. B-spline analysis can be utilized for different signal/imaging applications such as compression, prediction, and denoising. The exquisite features of wavelet transforms are utilized in the area of image processing which perform better compared to other transforms. Simulated noise images are used to evaluate the denoising performance of b-spline wavelets with the help of Bayes Shrink algorithm and along with another wavelet-based denoising like Cohen-Daubechies-Feauveau (CDF 9/7). It is shown through experimental results that, for certain images and input noise levels, the orthogonal b-splines give the best peak signal-to-noise ratio (PSNR), as compared to standard wavelet bases (Daubechies wavelets). Illustrative results that demonstrate the difference in efficiency of the approaches are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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