Description
Image processing comprises a broad variety of methods that operate on images to produce another image. A unique textbook, Introduction to Image Processing and Analysis establishes the programming involved in image processing and analysis by utilizing skills in C compiler and both Windows and MacOS programming environments. The provided mathematical background illustrates the workings of algorithms and emphasizes the practical reasons for using certain methods, their effects on images, and their appropriate applications. The text concentrates on image processing and measurement and details the implementation of many of the most widely used and most important image processing and analysis algorithms.
Homework problems are included in every chapter with solutions
available for download from the CRC Press website
The chapters work together to combine image processing with image analysis. The book begins with an explanation of familiar pixel array and goes on to describe the use of frequency space. Chapters 1 and 2 deal with the algorithms used in processing steps that are usually accomplished by a combination of measurement and processing operations, as described in chapters 3 and 4. The authors present each concept using a mixture of three mutually supportive tools: a description of the procedure with example images, the relevant mathematical equations behind each concept, and the simple source code (in C), which illustrates basic operations. In particularly, the source code provides a starting point to develop further modifications.
Written by John Russ, author of esteemed Image Processing Handbook now in its fifth edition, this book demonstrates functions to improve an image's of features and detail visibility, improve images for printing or transmission, and facilitate subsequent analysis.
Table of Contents
ADJUSTING PIXEL VALUES
Optimizing Contrast
Color Correction
Correcting Nonuniform Illumination
Geometric Transformations
Image Arithmetic
NEIGHBORHOOD OPERATIONS
Convolution
Other Neighborhood Operations
Statistical Operations
IMAGE PROCESSING IN THE FOURIER DOMAIN
The Fourier Transform
Removing Periodic Noise
Convolution and Correlation
Deconvolution
Other Transform Domains
Compression
BINARY IMAGES
Thresholding
Morphological Processing
Other Morphological Operations
Boolean Operations
MEASUREMENTS
Global Measurements
Feature Measurements
Classification
APPENDIX: SOFTWARE
REFERENCES AND LITERATURE INDEX
