Wavelets and their applications [[electronic resource] /] / edited by Michel Misiti ... [et al.] |
Autore | Misiti Michel |
Edizione | [1st edition] |
Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
Descrizione fisica | 1 online resource (354 p.) |
Disciplina |
515.2433
515/.2433 |
Altri autori (Persone) | MisitiMichel |
Collana | ISTE |
Soggetto topico | Wavelets (Mathematics) |
Soggetto genere / forma | Electronic books. |
ISBN |
1-280-84769-7
9786610847693 0-470-61249-5 0-470-39462-5 1-84704-581-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Wavelets and their Applications; Table of Contents; Notations; Introduction; Chapter 1. A Guided Tour; 1.1. Introduction; 1.2. Wavelets; 1.2.1. General aspects; 1.2.2. A wavelet; 1.2.3. Organization of wavelets; 1.2.4. The wavelet tree for a signal; 1.3. An electrical consumption signal analyzed by wavelets; 1.4. Denoising by wavelets: before and afterwards; 1.5. A Doppler signal analyzed by wavelets; 1.6. A Doppler signal denoised by wavelets; 1.7. An electrical signal denoised by wavelets; 1.8. An image decomposed by wavelets; 1.8.1. Decomposition in tree form
1.8.2. Decomposition in compact form1.9. An image compressed by wavelets; 1.10. A signal compressed by wavelets; 1.11. A fingerprint compressed using wavelet packets; Chapter 2. Mathematical Framework; 2.1. Introduction; 2.2. From the Fourier transform to the Gabor transform; 2.2.1. Continuous Fourier transform; 2.2.2. The Gabor transform; 2.3. The continuous transform in wavelets; 2.4. Orthonormal wavelet bases; 2.4.1. From continuous to discrete transform; 2.4.2. Multi-resolution analysis and orthonormal wavelet bases; 2.4.3. The scaling function and the wavelet; 2.5. Wavelet packets 2.5.1. Construction of wavelet packets2.5.2. Atoms of wavelet packets; 2.5.3. Organization of wavelet packets; 2.6. Biorthogonal wavelet bases; 2.6.1. Orthogonality and biorthogonality; 2.6.2. The duality raises several questions; 2.6.3. Properties of biorthogonal wavelets; 2.6.4. Semi-orthogonal wavelets; Chapter 3. From Wavelet Bases to the Fast Algorithm; 3.1. Introduction; 3.2. From orthonormal bases to the Mallat algorithm; 3.3. Four filters; 3.4. Efficient calculation of the coefficients; 3.5. Justification: projections and twin scales; 3.5.1. The decomposition phase 3.5.2. The reconstruction phase3.5.3. Decompositions and reconstructions of a higher order; 3.6. Implementation of the algorithm; 3.6.1. Initialization of the algorithm; 3.6.2. Calculation on finite sequences; 3.6.3. Extra coefficients; 3.7. Complexity of the algorithm; 3.8. From 1D to 2D; 3.9. Translation invariant transform; 3.9.1. ε -decimated DWT; 3.9.2. Calculation of the SWT; 3.9.3. Inverse SWT; Chapter 4. Wavelet Families; 4.1. Introduction; 4.2. What could we want from a wavelet?; 4.3. Synoptic table of the common families; 4.4. Some well known families 4.4.1. Orthogonal wavelets with compact support4.4.1.1. Daubechies wavelets: dbN; 4.4.1.2. Symlets: symN; 4.4.1.3. Coiflets: coifN; 4.4.2. Biorthogonal wavelets with compact support: bior; 4.4.3. Orthogonal wavelets with non-compact support; 4.4.3.1. The Meyer wavelet: meyr; 4.4.3.2. An approximation of the Meyer wavelet: dmey; 4.4.3.3. Battle and Lemarié wavelets: btlm; 4.4.4. Real wavelets without filters; 4.4.4.1. The Mexican hat: mexh; 4.4.4.2. The Morlet wavelet: morl; 4.4.4.3. Gaussian wavelets: gausN; 4.4.5. Complex wavelets without filters; 4.4.5.1. Complex Gaussian wavelets: cgau 4.4.5.2. Complex Morlet wavelets: cmorl |
Record Nr. | UNINA-9910143315503321 |
Misiti Michel
![]() |
||
London ; ; Newport Beach, CA, : ISTE, 2007 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Wavelets and their applications [[electronic resource] /] / edited by Michel Misiti ... [et al.] |
Autore | Misiti Michel |
Edizione | [1st edition] |
Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
Descrizione fisica | 1 online resource (354 p.) |
Disciplina |
515.2433
515/.2433 |
Altri autori (Persone) | MisitiMichel |
Collana | ISTE |
Soggetto topico | Wavelets (Mathematics) |
ISBN |
1-280-84769-7
9786610847693 0-470-61249-5 0-470-39462-5 1-84704-581-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Wavelets and their Applications; Table of Contents; Notations; Introduction; Chapter 1. A Guided Tour; 1.1. Introduction; 1.2. Wavelets; 1.2.1. General aspects; 1.2.2. A wavelet; 1.2.3. Organization of wavelets; 1.2.4. The wavelet tree for a signal; 1.3. An electrical consumption signal analyzed by wavelets; 1.4. Denoising by wavelets: before and afterwards; 1.5. A Doppler signal analyzed by wavelets; 1.6. A Doppler signal denoised by wavelets; 1.7. An electrical signal denoised by wavelets; 1.8. An image decomposed by wavelets; 1.8.1. Decomposition in tree form
1.8.2. Decomposition in compact form1.9. An image compressed by wavelets; 1.10. A signal compressed by wavelets; 1.11. A fingerprint compressed using wavelet packets; Chapter 2. Mathematical Framework; 2.1. Introduction; 2.2. From the Fourier transform to the Gabor transform; 2.2.1. Continuous Fourier transform; 2.2.2. The Gabor transform; 2.3. The continuous transform in wavelets; 2.4. Orthonormal wavelet bases; 2.4.1. From continuous to discrete transform; 2.4.2. Multi-resolution analysis and orthonormal wavelet bases; 2.4.3. The scaling function and the wavelet; 2.5. Wavelet packets 2.5.1. Construction of wavelet packets2.5.2. Atoms of wavelet packets; 2.5.3. Organization of wavelet packets; 2.6. Biorthogonal wavelet bases; 2.6.1. Orthogonality and biorthogonality; 2.6.2. The duality raises several questions; 2.6.3. Properties of biorthogonal wavelets; 2.6.4. Semi-orthogonal wavelets; Chapter 3. From Wavelet Bases to the Fast Algorithm; 3.1. Introduction; 3.2. From orthonormal bases to the Mallat algorithm; 3.3. Four filters; 3.4. Efficient calculation of the coefficients; 3.5. Justification: projections and twin scales; 3.5.1. The decomposition phase 3.5.2. The reconstruction phase3.5.3. Decompositions and reconstructions of a higher order; 3.6. Implementation of the algorithm; 3.6.1. Initialization of the algorithm; 3.6.2. Calculation on finite sequences; 3.6.3. Extra coefficients; 3.7. Complexity of the algorithm; 3.8. From 1D to 2D; 3.9. Translation invariant transform; 3.9.1. ε -decimated DWT; 3.9.2. Calculation of the SWT; 3.9.3. Inverse SWT; Chapter 4. Wavelet Families; 4.1. Introduction; 4.2. What could we want from a wavelet?; 4.3. Synoptic table of the common families; 4.4. Some well known families 4.4.1. Orthogonal wavelets with compact support4.4.1.1. Daubechies wavelets: dbN; 4.4.1.2. Symlets: symN; 4.4.1.3. Coiflets: coifN; 4.4.2. Biorthogonal wavelets with compact support: bior; 4.4.3. Orthogonal wavelets with non-compact support; 4.4.3.1. The Meyer wavelet: meyr; 4.4.3.2. An approximation of the Meyer wavelet: dmey; 4.4.3.3. Battle and Lemarié wavelets: btlm; 4.4.4. Real wavelets without filters; 4.4.4.1. The Mexican hat: mexh; 4.4.4.2. The Morlet wavelet: morl; 4.4.4.3. Gaussian wavelets: gausN; 4.4.5. Complex wavelets without filters; 4.4.5.1. Complex Gaussian wavelets: cgau 4.4.5.2. Complex Morlet wavelets: cmorl |
Record Nr. | UNISA-996216942303316 |
Misiti Michel
![]() |
||
London ; ; Newport Beach, CA, : ISTE, 2007 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
Wavelets and their applications [[electronic resource] /] / edited by Michel Misiti ... [et al.] |
Autore | Misiti Michel |
Edizione | [1st edition] |
Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
Descrizione fisica | 1 online resource (354 p.) |
Disciplina |
515.2433
515/.2433 |
Altri autori (Persone) | MisitiMichel |
Collana | ISTE |
Soggetto topico | Wavelets (Mathematics) |
ISBN |
1-280-84769-7
9786610847693 0-470-61249-5 0-470-39462-5 1-84704-581-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Wavelets and their Applications; Table of Contents; Notations; Introduction; Chapter 1. A Guided Tour; 1.1. Introduction; 1.2. Wavelets; 1.2.1. General aspects; 1.2.2. A wavelet; 1.2.3. Organization of wavelets; 1.2.4. The wavelet tree for a signal; 1.3. An electrical consumption signal analyzed by wavelets; 1.4. Denoising by wavelets: before and afterwards; 1.5. A Doppler signal analyzed by wavelets; 1.6. A Doppler signal denoised by wavelets; 1.7. An electrical signal denoised by wavelets; 1.8. An image decomposed by wavelets; 1.8.1. Decomposition in tree form
1.8.2. Decomposition in compact form1.9. An image compressed by wavelets; 1.10. A signal compressed by wavelets; 1.11. A fingerprint compressed using wavelet packets; Chapter 2. Mathematical Framework; 2.1. Introduction; 2.2. From the Fourier transform to the Gabor transform; 2.2.1. Continuous Fourier transform; 2.2.2. The Gabor transform; 2.3. The continuous transform in wavelets; 2.4. Orthonormal wavelet bases; 2.4.1. From continuous to discrete transform; 2.4.2. Multi-resolution analysis and orthonormal wavelet bases; 2.4.3. The scaling function and the wavelet; 2.5. Wavelet packets 2.5.1. Construction of wavelet packets2.5.2. Atoms of wavelet packets; 2.5.3. Organization of wavelet packets; 2.6. Biorthogonal wavelet bases; 2.6.1. Orthogonality and biorthogonality; 2.6.2. The duality raises several questions; 2.6.3. Properties of biorthogonal wavelets; 2.6.4. Semi-orthogonal wavelets; Chapter 3. From Wavelet Bases to the Fast Algorithm; 3.1. Introduction; 3.2. From orthonormal bases to the Mallat algorithm; 3.3. Four filters; 3.4. Efficient calculation of the coefficients; 3.5. Justification: projections and twin scales; 3.5.1. The decomposition phase 3.5.2. The reconstruction phase3.5.3. Decompositions and reconstructions of a higher order; 3.6. Implementation of the algorithm; 3.6.1. Initialization of the algorithm; 3.6.2. Calculation on finite sequences; 3.6.3. Extra coefficients; 3.7. Complexity of the algorithm; 3.8. From 1D to 2D; 3.9. Translation invariant transform; 3.9.1. ε -decimated DWT; 3.9.2. Calculation of the SWT; 3.9.3. Inverse SWT; Chapter 4. Wavelet Families; 4.1. Introduction; 4.2. What could we want from a wavelet?; 4.3. Synoptic table of the common families; 4.4. Some well known families 4.4.1. Orthogonal wavelets with compact support4.4.1.1. Daubechies wavelets: dbN; 4.4.1.2. Symlets: symN; 4.4.1.3. Coiflets: coifN; 4.4.2. Biorthogonal wavelets with compact support: bior; 4.4.3. Orthogonal wavelets with non-compact support; 4.4.3.1. The Meyer wavelet: meyr; 4.4.3.2. An approximation of the Meyer wavelet: dmey; 4.4.3.3. Battle and Lemarié wavelets: btlm; 4.4.4. Real wavelets without filters; 4.4.4.1. The Mexican hat: mexh; 4.4.4.2. The Morlet wavelet: morl; 4.4.4.3. Gaussian wavelets: gausN; 4.4.5. Complex wavelets without filters; 4.4.5.1. Complex Gaussian wavelets: cgau 4.4.5.2. Complex Morlet wavelets: cmorl |
Record Nr. | UNINA-9910830843103321 |
Misiti Michel
![]() |
||
London ; ; Newport Beach, CA, : ISTE, 2007 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Wavelets and their applications / / edited by Michel Misiti ... [et al.] |
Edizione | [1st edition] |
Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
Descrizione fisica | 1 online resource (354 p.) |
Disciplina | 515/.2433 |
Altri autori (Persone) | MisitiMichel |
Collana | ISTE |
Soggetto topico | Wavelets (Mathematics) |
ISBN |
1-280-84769-7
9786610847693 0-470-61249-5 0-470-39462-5 1-84704-581-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Wavelets and their Applications; Table of Contents; Notations; Introduction; Chapter 1. A Guided Tour; 1.1. Introduction; 1.2. Wavelets; 1.2.1. General aspects; 1.2.2. A wavelet; 1.2.3. Organization of wavelets; 1.2.4. The wavelet tree for a signal; 1.3. An electrical consumption signal analyzed by wavelets; 1.4. Denoising by wavelets: before and afterwards; 1.5. A Doppler signal analyzed by wavelets; 1.6. A Doppler signal denoised by wavelets; 1.7. An electrical signal denoised by wavelets; 1.8. An image decomposed by wavelets; 1.8.1. Decomposition in tree form
1.8.2. Decomposition in compact form1.9. An image compressed by wavelets; 1.10. A signal compressed by wavelets; 1.11. A fingerprint compressed using wavelet packets; Chapter 2. Mathematical Framework; 2.1. Introduction; 2.2. From the Fourier transform to the Gabor transform; 2.2.1. Continuous Fourier transform; 2.2.2. The Gabor transform; 2.3. The continuous transform in wavelets; 2.4. Orthonormal wavelet bases; 2.4.1. From continuous to discrete transform; 2.4.2. Multi-resolution analysis and orthonormal wavelet bases; 2.4.3. The scaling function and the wavelet; 2.5. Wavelet packets 2.5.1. Construction of wavelet packets2.5.2. Atoms of wavelet packets; 2.5.3. Organization of wavelet packets; 2.6. Biorthogonal wavelet bases; 2.6.1. Orthogonality and biorthogonality; 2.6.2. The duality raises several questions; 2.6.3. Properties of biorthogonal wavelets; 2.6.4. Semi-orthogonal wavelets; Chapter 3. From Wavelet Bases to the Fast Algorithm; 3.1. Introduction; 3.2. From orthonormal bases to the Mallat algorithm; 3.3. Four filters; 3.4. Efficient calculation of the coefficients; 3.5. Justification: projections and twin scales; 3.5.1. The decomposition phase 3.5.2. The reconstruction phase3.5.3. Decompositions and reconstructions of a higher order; 3.6. Implementation of the algorithm; 3.6.1. Initialization of the algorithm; 3.6.2. Calculation on finite sequences; 3.6.3. Extra coefficients; 3.7. Complexity of the algorithm; 3.8. From 1D to 2D; 3.9. Translation invariant transform; 3.9.1. ε -decimated DWT; 3.9.2. Calculation of the SWT; 3.9.3. Inverse SWT; Chapter 4. Wavelet Families; 4.1. Introduction; 4.2. What could we want from a wavelet?; 4.3. Synoptic table of the common families; 4.4. Some well known families 4.4.1. Orthogonal wavelets with compact support4.4.1.1. Daubechies wavelets: dbN; 4.4.1.2. Symlets: symN; 4.4.1.3. Coiflets: coifN; 4.4.2. Biorthogonal wavelets with compact support: bior; 4.4.3. Orthogonal wavelets with non-compact support; 4.4.3.1. The Meyer wavelet: meyr; 4.4.3.2. An approximation of the Meyer wavelet: dmey; 4.4.3.3. Battle and Lemarié wavelets: btlm; 4.4.4. Real wavelets without filters; 4.4.4.1. The Mexican hat: mexh; 4.4.4.2. The Morlet wavelet: morl; 4.4.4.3. Gaussian wavelets: gausN; 4.4.5. Complex wavelets without filters; 4.4.5.1. Complex Gaussian wavelets: cgau 4.4.5.2. Complex Morlet wavelets: cmorl |
Record Nr. | UNINA-9910877775003321 |
London ; ; Newport Beach, CA, : ISTE, 2007 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|