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008			190118s2018 nyua ob 001 0 eng d
015			_aGBC2L2843 _2bnb
020			_a978935062989 (Pbk)
037			_a9781292223070 _bPearson UK
040			_aYDX _beng _cIISERB _erda _epn
042			_aukblsr
050		4	_aTA1632 _b.G66 2018
072		7	_aTHR _2bicssc
082	0	4	_a621.367 G589D4 _223
100	1		_aGonzalez, Rafael C. _929155
245	1	0	_aDigital image processing _cRafael C. Gonzalez, Richard E. Woods.
250			_aFourth edition.
260			_aChennai: _bPearson India Education, _c2023.
300			_a1019 pages : _billustrations (some color).
504			_aIncludes bibliographical references (pages 995-1007) and index.
505	0		_a1 Introduction 1.1 What is Digital Image Processing? 1.2 The Origins of Digital Image Processing 1.3 Examples of Fields that Use Digital Image Processing 1.4 Fundamental Steps in Digital Image Processing 1.5 Components of an Image Processing System 2 Digital Image Fundamentals 2.1 Elements of Visual Perception 2.2 Light and the Electromagnetic Spectrum 2.3 Image Sensing and Acquisition 2.4 Image Sampling and Quantization 2.5 Some Basic Relationships Between Pixels 2.6 Introduction to the Basic Mathematical Tools Used in Digital Image Processing 3 Intensity Transformations and Spatial Filtering 3.1 Background 3.2 Some Basic Intensity Transformation Functions 3.3 Histogram Processing 3.4 Fundamentals of Spatial Filtering 3.5 Smoothing (Lowpass) Spatial Filters 3.6 Sharpening (Highpass) Spatial Filters 3.7 Highpass, Bandreject, and Bandpass Filters from Lowpass Filters 3.8 Combining Spatial Enhancement Methods 3.9 Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering 4 Filtering in the Frequency Domain 4.1 Background 4.2 Preliminary Concepts 4.3 Sampling and the Fourier Transform of Sampled Functions 4.4 The Discrete Fourier Transform of One Variable 4.5 Extensions to Functions of Two Variables 4.6 Some Properties of the 2-D DFT and IDFT 4.7 The Basics of Filtering in the Frequency Domain 4.8 Image Smoothing Using Lowpass Frequency Domain Filters 4.9 Image Sharpening Using Highpass Filters 4.10 Selective Filtering 4.11 The Fast Fourier Transform 5 Image Restoration and Reconstruction 5.1 A Model of the Image Degradation/Restoration Process 5.2 Noise Models 5.3 Restoration in the Presence of Noise Only—Spatial Filtering 5.4 Periodic Noise Reduction Using Frequency Domain Filtering 5.5 Linear, Position-Invariant Degradations 5.6 Estimating the Degradation Function 5.7 Inverse Filtering 5.8 Minimum Mean Square Error (Wiener) Filtering 5.9 Constrained Least Squares Filtering 5.10 Geometric Mean Filter 5.11 Image Reconstruction from Projections 6 Wavelet and Other Image Transforms 6.1 Preliminaries 6.2 Matrix-based Transforms 6.3 Correlation 6.4 Basis Functions in the Time-Frequency Plane 6.5 Basis Images 6.6 Fourier-Related Transforms 6.7 Walsh-Hadamard Transforms 6.8 Slant Transform 6.9 Haar Transform 6.10 Wavelet Transforms 7 Color Image Processing 7.1 Color Fundamentals 7.2 Color Models 7.3 Pseudocolor Image Processing 7.4 Basics of Full-Color Image Processing 7.5 Color Transformations 7.6 Color Image Smoothing and Sharpening 7.7 Using Color in Image Segmentation 7.8 Noise in Color Images 7.9 Color Image Compression 8 Image Compression and Watermarking 8.1 Fundamentals 8.2 Huffman Coding 8.3 Golomb Coding 8.4 Arithmetic Coding 8.5 LZW Coding 8.6 Run-length Coding.
650		0	_aImage processing _xDigital techniques. _929156
650		6	_aTraitement d'images _xTechniques numériques. _929157
650		7	_adigital imaging. _2aat _929158
650		7	_aImage processing _xDigital techniques. _2fast _929156
700	1		_aWoods, Richard E. _929159
903			_aELD.DS.725762
942			_2ddc _cBK
999			_c10000 _d10000