Adaptive Lifting Scheme for Nonseparable Two-Dimensional Wavelet Transforms (CROSBI ID 345631)
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Podaci o odgovornosti
Vrankić, Miroslav
Seršić, Damir
engleski
Adaptive Lifting Scheme for Nonseparable Two-Dimensional Wavelet Transforms
In this thesis, we propose the novel adaptive wavelet filter bank structures that are used to obtain efficient representations of the analyzed images. We present the lifting scheme structures for building adaptive wavelet decompositions based on the nonseparable quincunx sampling scheme. The resulting wavelet decompositions are adaptive to the local properties of the analyzed image. Despite the introduced adaptation, a desired number of vanishing moments is still retained. The proposed adaptation is performed in order to minimize the energy of detail coefficients on a neighborhood of each pixel of the analyzed image. The appropriate neighborhood is determined for each pixel separately by using the intersection of confidence intervals (ICI) rule. The application of the ICI rule improves the estimation of the filter bank parameters and makes it more robust to noise. The image denoising results are presented for both synthetic and real-world images. It is shown that the adaptive wavelet decompositions outperform the existing fixed decompositions in terms of denoising quality of images that contain periodic components, and in general they give more compact image representations.
wavelet transforms; adaptive filters; second generation wavelets; adaptive lifting scheme; quincunx sampling; interpolating filters; intersection of confidence intervals; image denoising
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165
06.07.2006.
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