LEADER 04426nam 2200505za 450 001 9911019285303321 005 20230120072414.0 010 $a9781118979310 010 $a1118979311 010 $a9781119555414 010 $a1119555418 010 $a9781118979327 010 $a111897932X 035 $a(MiAaPQ)EBC5747373 035 $a(PPN)271976314 035 $a(OCoLC)1073883387 035 $a(CaSebORM)9781118979273 035 $a(CKB)4100000007926688 035 $a(Perlego)2759646 035 $a(EXLCZ)994100000007926688 100 $a20190423d2019 uy 0 101 0 $aeng 135 $aurcn|nnn||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiscrete wavelet transformations $ean elementary approach with applications /$fPatrick J. Van Fleet 205 $a2nd ed. 210 $aHoboken, N.J. $cWiley$d2019 215 $a1 online resource (xxvii, 587 p.) $cill 300 $aPrevious ed.: 2008. 311 08$aPrint version: Van Fleet, Patrick J., 1962- author. Discrete wavelet transformations 2nd edition. Hoboken, NJ : John Wiley & Sons, Inc., [2019] 9781118979273 (DLC) 2018046966 320 $aIncludes bibliographical references and index. 327 $a1. Introduction : why wavelets? -- 2. Vectors and matrices -- 3. An introduction to digital images -- 4. The haar wavelet transformation -- 5. Daubechies wavelet transformations -- 6. Wavelet shrinkage : an application to denoising -- 7. Biorthogonal wavelet transformations -- 8. Complex numbers and Fourier series -- 9. Filter construction in the Fourier domain -- 10. Wavelet packets -- 11. Lifting -- 12. The JPEG2000 image compression standard -- A. Basic statistics. 330 $aThe new edition of Discrete Wavelet Transformations continues to guide readers through the abstract concepts of wavelet theory by using Dr. Van Fleet?s highly practical, application-based approach, which reflects how mathematicians construct solutions to challenges outside the classroom. By introducing the Haar, orthogonal, and biorthogonal filters without the use of Fourier series, Van Fleet allows his audience to connect concepts directly to real-world applications at an earlier point than other publications in the field. Leveraging extensive graphical displays, this self-contained volume integrates concepts from calculus and linear algebra into the constructions of wavelet transformations and their applications, including data compression, edge detection in images and denoising of signals. Conceptual understanding is reinforced with over 500 detailed exercises and 24 computer labs. The second edition discusses new applications including image segmentation, pansharpening, and the FBI fingerprint compression specification. Other notable features include: Two new chapters covering wavelet packets and the lifting method; A reorganization of the presentation so that basic filters can be constructed without the use of Fourier techniques; A new comprehensive chapter that explains filter derivation using Fourier techniques; Over 120 examples of which 91 are ?live examples,? which allow the reader to quickly reproduce these examples in Mathematica or MATLAB and deepen conceptual mastery; An overview of digital image basics, equipping readers with the tools they need to understand the image processing applications presented; A complete rewrite of the DiscreteWavelets package called WaveletWare for use with Mathematica and MATLAB; A website, www.stthomas.edu/wavelets, featuring material containing the WaveletWare package, live examples, and computer labs in addition to companion material for teaching a course using the book. Comprehensive and grounded, this book and its online components provide an excellent foundation for developing undergraduate courses as well as a valuable resource for mathematicians, signal process engineers, and other professionals seeking to understand the practical applications of discrete wavelet transformations in solving real-world challenges. 606 $aWavelets (Mathematics) 606 $aTransformations (Mathematics) 615 0$aWavelets (Mathematics) 615 0$aTransformations (Mathematics) 676 $a515.2433 700 $aVan Fleet$b Patrick J.$f1962-$0521988 906 $aBOOK 912 $a9911019285303321 996 $aDiscrete wavelet transformations$9835247 997 $aUNINA