LEADER 02519nam 2200457 a 450 001 9910958488903321 005 20240313140440.0 010 0 $a9781118337837 010 0 $a1118337832 035 $a(MiAaPQ)EBC7103554 035 $a(CKB)24989714100041 035 $a(MiAaPQ)EBC1120699 035 $a(Au-PeEL)EBL1120699 035 $a(CaPaEBR)ebr10657809 035 $a(CaONFJC)MIL447066 035 $a(OCoLC)827207600 035 $a(Perlego)1002630 035 $a(EXLCZ)9924989714100041 100 $a20130118d2013 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aChristian history $ean introduction /$fAlister E. McGrath 205 $a1st ed. 210 $aHoboken $cWiley-Blackwell$d2013 215 $axviii, 374 p. $cill., maps 320 $aIncludes bibliographical references and index. 327 $aThe early church, 100-500 -- The Middle Ages and Renaissance, c. 500-c. 1500 -- Competing visions of reform, c.1500-c.1650 -- The modern age, c.1650-1914 -- The twentieth century, 1914 to the present. 330 $aA major new introduction to the global history of Christianity, written by one of the world's leading theologians and author of numerous bestselling textbooks.  Provides a truly global review by exploring the development of Christianity and related issues in Asia, Latin America and Africa, and not just focusing on Western concerns Spanning more than two millennia and combining elements of theology, history, and culture, it traces the development of all three branches of Christianity - Catholic, Protestant, and Orthodox - providing context to Christianity's origins and its links to Judaism Looks beyond denominational history at Christianity's impact on individuals, society, politics, and intellectual thought, as well as on art, architecture, and the natural sciences Combines McGrath's acute historical sensibility with formidable organizational skill, breaking the material down into accessible, self-contained historical periods Offers an accessible and student-oriented text, assuming little or no advance theological or historical knowledge on the part of the reader. 606 $aChurch history 615 0$aChurch history. 676 $a270 700 $aMcGrath$b Alister E.$f1953-$0868809 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910958488903321 996 $aChristian history$94353800 997 $aUNINA LEADER 06395nam 22005293 450 001 9911019324003321 005 20240607080433.0 010 $a9781119617778 010 $a1119617774 010 $a9781119617754 010 $a1119617758 035 $a(MiAaPQ)EBC31368819 035 $a(Au-PeEL)EBL31368819 035 $a(CKB)32238909000041 035 $a(Perlego)4442241 035 $a(OCoLC)1438670922 035 $a(EXLCZ)9932238909000041 100 $a20240607d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDigital Image Denoising in MATLAB 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2024. 210 4$dİ2024. 215 $a1 online resource (227 pages) 225 1 $aIEEE Press Series 311 08$a9781119617693 311 08$a1119617693 327 $aCover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Acknowledgments -- Nomenclature -- About the Companion Website -- Chapter 1 Digital Image -- 1.1 Color Image -- 1.1.1 Color Filter Array and Demosaicing -- 1.1.2 Perceptual Color Space -- 1.1.3 Grayscale Image -- 1.2 Alternate Domain Image Representation -- 1.3 Digital Imaging in MATLAB -- 1.4 Current Pixel and Neighboring Pixels -- 1.4.1 Boundary Extension -- 1.5 Digital Image Noise -- 1.5.1 Random Noise -- 1.5.2 Gaussian Noise -- 1.5.2.1 Noise Power Estimation -- 1.5.2.2 Noise Power Estimation Base on Derivative -- 1.5.3 Salt and Pepper Noise -- 1.6 Mixed Noise -- 1.7 Performance Evaluation -- 1.8 Image Quality Measure -- 1.8.1 Mean Squares Error -- 1.8.2 Peak Signal?to?Noise Ratio -- 1.8.3 Texture and Flat PSNR -- 1.8.4 Texture Area Classification -- 1.9 Structural Similarity -- 1.10 Brightness Normalization -- 1.11 Summary -- Exercises -- Chapter 2 Filtering -- 2.1 Mean Filter -- 2.1.1 Gaussian Smoothing -- 2.2 Wiener Filter -- 2.3 Transform Thresholding -- 2.3.1 Overlapped Block -- 2.4 Median Filter -- 2.4.1 Noise Reduction Performance -- 2.4.2 Adaptive Median Filter -- 2.4.3 Median Filter with Predefined Mask -- 2.4.4 Median of Median -- 2.5 Summary -- Exercises -- Chapter 3 Wavelet -- 3.1 2D Wavelet Transform -- 3.2 Noise Estimation -- 3.3 Wavelet Denoise -- 3.4 Thresholding -- 3.4.1 Threshold Function -- 3.5 Threshold Value -- 3.5.1 Universal Threshold (Donoho Threshold) -- 3.5.1.1 Adaptive Threshold -- 3.6 Wavelet Wiener -- 3.7 Cycle Spinning -- 3.8 Fusion -- 3.8.1 Baseband Image Fusion -- 3.8.1.1 Simple Average -- 3.8.1.2 Arithmetic Combination -- 3.8.1.3 Correlation Base -- 3.8.2 Detail Images Fusion -- 3.8.2.1 Simple Average -- 3.8.2.2 Select Max -- 3.8.2.3 Cross Band Fusion -- 3.9 Which Wavelets to Use -- 3.10 Summary -- Exercises. 327 $aChapter 4 Rank Minimization -- 4.1 Singular Value Decomposition (SVD) -- 4.2 Threshold Denoising Through AWGN Analysis -- 4.2.1 Noise Estimation -- 4.2.2 Denoising Performance -- 4.3 Blocked SVD -- 4.4 The Randomized Algorithm -- 4.4.1 Iterative Adjustment -- 4.5 Summary -- Exercises -- Chapter 5 Variational Method -- 5.1 Total Variation -- 5.1.1 Rudin-Osher-Fatemi (ROF) Model -- 5.1.2 Le-Chartrand-Asaki (LCA) Model -- 5.1.3 Aubert-Aujol (AA) Model -- 5.2 Gradient Descent ROF TV Algorithm -- 5.2.1 Finite Difference Method -- 5.3 Staircase Noise Artifacts -- 5.4 Summary -- Exercises -- Chapter 6 NonLocal Means -- 6.1 NonLocal Means -- 6.1.1 Hard Threshold -- 6.2 Adaptive Window Size -- 6.2.1 Patch Window Size Adaptation -- 6.2.2 Search Window Size Adaptation -- 6.3 Summary -- Exercises -- Chapter 7 Random Sampling -- 7.1 Averaging Multiple Copies of Noisy Images -- 7.2 Missing Pixels and Inpainting -- 7.3 Singular Value Thresholding Inpainting -- 7.4 Wavelet Image Fusion -- 7.5 Summary -- Exercises -- Appendix A MATLAB Functions List -- References -- Index -- EULA. 330 $a"Presents a review of image denoising algorithms with practical MATLAB implementation guidance Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB. This hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book. The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions. Explains how the quality of an image can be quantified in MATLAB Discusses what constitutes a "naturally looking" image in subjective and analytical terms Presents denoising techniques for a wide range of digital image processing applications Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis Requires only a fundamental knowledge of digital signal processing Includes access to a companion website with source codes, exercises, and additional resources Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques"--$cProvided by publisher. 410 0$aIEEE Press Series 606 $aImage processing$xDigital techniques 615 0$aImage processing$xDigital techniques. 676 $a006.6 700 $aKok$b Chi-Wah$01638178 701 $aTam$b Wing-Shan$01667930 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019324003321 996 $aDigital Image Denoising in MATLAB$94416160 997 $aUNINA