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Digital Image Processing, Global Edition

Digital Image Processing, Global Edition

Wydawnictwo Pearson Education
Data wydania 01/11/2017
Wydanie Czwarte
Liczba stron 1024
Forma publikacji książka w miękkiej oprawie
Poziom zaawansowania Dla szkół wyższych i kształcenia podyplomowego
Język angielski
ISBN 9781292223049
Kategorie Inżynieria elektryczna, Przetwarzanie obrazu
289.00 PLN (z VAT)
$78.85 / €68.17 / £59.96 /
Produkt dostępny
Przesyłka w 2 dni
Do schowka

Opis książki

For courses in Image Processing and Computer Vision. Introduce your students to image processing with the industry's most prized textFor 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. As in all earlier editions, the focus of this edition of the book is on fundamentals. The 4th Edition, which celebrates the book's 40th anniversary, is based on an extensive survey of faculty, students, and independent readers in 150 institutions from 30 countries. Their feedback led to expanded or new coverage of topics such as deep learning and deep neural networks, including convolutional neural nets, the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering and superpixels, active contours (snakes and level sets), and exact histogram matching. Major improvements were made in reorganizing the material on image transforms into a more cohesive presentation, and in the discussion of spatial kernels and spatial filtering. Major revisions and additions were made to examples and homework exercises throughout the book. For the first time, we added MATLAB projects at the end of every chapter, and compiled support packages for students and faculty containing, solutions, image databases, and sample code.

Digital Image Processing, Global Edition

Spis treści

1 Introduction1.1 What is Digital Image Processing?1.2 The Origins of Digital Image Processing1.3 Examples of Fields that Use Digital Image Processing Gamma-Ray Imaging X-Ray Imaging Imaging in the Ultraviolet Band Imaging in the Visible and Infrared Bands Imaging in the Microwave Band Imaging in the Radio Band Other Imaging Modalities1.4 Fundamental Steps in Digital Image Processing1.5 Components of an Image Processing System2 Digital Image Fundamentals2.1 Elements of Visual Perception Structure of the Human Eye Image Formation in the Eye Brightness Adaptation and Discrimination2.2 Light and the Electromagnetic Spectrum2.3 Image Sensing and Acquisition Image Acquisition Using a Single Sensing Element Image Acquisition Using Sensor Strips Image Acquisition Using Sensor Arrays A Simple Image Formation Model2.4 Image Sampling and Quantization Basic Concepts in Sampling and Quantization Representing Digital Images Linear vs. Coordinate Indexing Spatial and Intensity Resolution Image Interpolation2.5 Some Basic Relationships Between Pixels Neighbors of a Pixel Adjacency, Connectivity, Regions, and Boundaries Distance Measures2.6 Introduction to the Basic Mathematical Tools Used in Digital Image Processing Elementwise versus Matrix Operations Linear versus Nonlinear Operations Arithmetic Operations Set and Logical Operations Basic Set Operations Logical Operations Fuzzy Sets Spatial Operations Single-Pixel Operations Neighborhood Operations Geometric Transformations Image Registration Vector and Matrix Operations Image Transforms Probability and Random Variables3 Intensity Transformations and Spatial Filtering3.1 Background The Basics of Intensity Transformations and Spatial Filtering About the Examples in this Chapter3.2 Some Basic Intensity Transformation Functions Image Negatives Log Transformations Power-Law (Gamma) Transformations Piecewise Linear Transformation Functions Contrast Stretching Intensity-Level Slicing Bit-Plane Slicing3.3 Histogram Processing Histogram Equalization Histogram Matching (Specification) Exact Histogram Matching (Specification) Foundation Ordering Computing the neighborhood averages and extracting the K-tuples: Exact Histogram Specification Algorithm Local Histogram Processing Using Histogram Statistics for Image Enhancement3.4 Fundamentals of Spatial Filtering The Mechanics of Linear Spatial Filtering Spatial Correlation and Convolution Separable Filter Kerne

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