LEADER 05857nam 2200721 a 450 001 9910451061703321 005 20200520144314.0 010 $a1-281-91870-9 010 $a9786611918705 010 $a981-270-906-1 035 $a(CKB)1000000000404711 035 $a(EBL)1679391 035 $a(OCoLC)879074202 035 $a(SSID)ssj0000199216 035 $a(PQKBManifestationID)11954305 035 $a(PQKBTitleCode)TC0000199216 035 $a(PQKBWorkID)10184533 035 $a(PQKB)10936734 035 $a(MiAaPQ)EBC1679391 035 $a(WSP)00006540 035 $a(Au-PeEL)EBL1679391 035 $a(CaPaEBR)ebr10255453 035 $a(CaONFJC)MIL191870 035 $a(EXLCZ)991000000000404711 100 $a20070510d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMathematics and computation in imaging science and information processing$b[electronic resource] /$feditors Say Song Goh, Amos Ron, Zuowei Shen 210 $aNew Jersey $cWorld Scientific$dc2007 215 $a1 online resource (276 p.) 225 1 $aLecture notes series, Institute for Mathematical Sciences, National University of Singapore ;$vv. 11 300 $aDescription based upon print version of record. 311 $a981-270-905-3 320 $aIncludes bibliographical references. 327 $aCONTENTS; Foreword; Preface; Subdivision on Arbitrary Meshes: Algorithms and Theory Denis Zorin; 1. Introduction; 1.1. Subdivision in computer graphics and geometric modeling; 2. Basics; 2.1. Subdivision curves; 2.2. Subdivision surfaces; 3. Overview of Subdivision Schemes; 3.1. Classification of subdivision schemes; 3.2. Loop scheme; 3.3. Catmull-Clark scheme; 4. Modified Buttery Scheme; 4.1. Doo-Sabin scheme; 4.2. Midedge scheme and other non-integer arity schemes; 4.3. Comparison; 5. Smoothness of Subdivision Surfaces; 5.1. Cr-continuity and tangent plane continuity 327 $a5.2. Universal surfaces5.3. Sufficient smoothness criteria; 6. Approximation Properties of Subdivision Surfaces; 6.1. Functional spaces on surfaces; 6.2. Manifold structure defined by subdivision; 7. Conclusions; References; High Order Numerical Methods for Time Dependent Hamilton-Jacobi Equations Chi-Wang Shu; 1. Introduction and Properties of Hamilton-Jacobi Equations; 2. First Order Monotone Schemes; 2.1. Monotone schemes on structured rectangular meshes; 2.2. Monotone schemes on unstructured meshes; 3. High Order ENO and WENO Schemes on Structured Rectangular Meshes 327 $a3.1. High order ENO schemes3.2. High order WENO schemes; 4. High Order WENO Schemes on Unstructured Meshes; 5. High Order Discontinuous Galerkin Schemes on Unstructured Meshes; 6. High Order Strong Stability Preserving Runge-Kutta Time Discretizations; 7. A Few Numerical Examples; 8. Concluding Remarks; References; Theory and Computation of Variational Image Deblurring Tony F. Chan and Jianhong Shen; 1. Mathematical Models of Blurs; 1.1. Linear blurs; 1.2. The DC-condition; 1.3. Nonlinear blurs; 2. Illposedness of Deblurring; 3. Tikhonov and Bayesian Regularization 327 $a4. Optimal Wiener Filtering for Non-Blind Deblurring4.1. 2-D stochastic spatial signals; 4.2. Stochastic signals as random generalized functions; 4.3. Filtering-based deblurring; 4.4. Optimal Wiener ltering; 4.5. Connection to the Bayesian/Tikhonov method; 5. Deblurring Blurred BV Images; 5.1. TV deblurring by Rudin, Osher, and Fatemi; 5.2. Dealing with bounded image domains; 5.3. Existence and uniqueness; 5.4. Computation and examples; 6. Parametric Blind Deblurring; 6.1. Parametric modeling; 6.2. The AM algorithm; 7. Non-Parametric Blind Deblurring: Double-BV Model 327 $a7.1. General formulation of blind deblurring7.2. Double-BV blind deblurring model of Chan and Wong; 7.3. On the uniqueness: Hidden symmetries; 7.4. The existence theorem; 8. Deblurring Besov Images via Iterated Shrinkage; 8.1. Wavelets and Besov images; 8.2. Besov image deblurring via iterated shrinkage; 8.3. Understanding the iterated-shrinkage algorithm; 8.3.1. As semi-implicit time marching; 8.3.2. Via augmentation and auxiliary variables; 9. Further Reading; Acknowledgements; References; Data Hiding - Theory and Algorithms Pierre Moulin and Ralf Koetter; 1. Introduction 327 $a2. Model for Data Hiding 330 $a The explosion of data arising from rapid advances in communication, sensing and computational power has concentrated research effort on more advanced techniques for the representation, processing, analysis and interpretation of data sets. In view of these exciting developments, the program "Mathematics and Computation in Imaging Science and Information Processing" was held at the Institute for Mathematical Sciences, National University of Singapore, from July to December 2003 and in August 2004 to promote and facilitate multidisciplinary research in the area. As part of the program, a series 410 0$aLecture notes series (National University of Singapore. Institute for Mathematical Sciences) ;$vv. 11. 606 $aImage processing$xMathematical models 606 $aImage processing$xData processing 606 $aElectronic data processing$xMathematical models 608 $aElectronic books. 615 0$aImage processing$xMathematical models. 615 0$aImage processing$xData processing. 615 0$aElectronic data processing$xMathematical models. 676 $a621.36/7 701 $aGoh$b Say Song$0863331 701 $aRon$b ?Amos$0863332 701 $aShen$b Zuowei$0863333 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910451061703321 996 $aMathematics and computation in imaging science and information processing$92139949 997 $aUNINA