Simplified Approach to Image Processing, A: Classical and Modern Techniques in C

About

Features

• Platform independant code. This insures that the reader can use the code no matter what computer or copier is being used.
• Treatment of color image processing. This book explains the need to convert from RGB to HSI colorspace.
• Presentation of Image Compression Techniques. Covers the older, current, and up-and-coming techniques.
• Presentation of Image Warping and Morphing Techniques.
  • Spatial transforms, Meshwarp algorithm, Field morphing algorithm.
• The Bibliography is a collection of highly used references.
• Appendix of Image processing resources lists organizations, conferences, publications, and sources of processing software and hardware.

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Description

• Copyright 1997
• Edition: 1st

• Book
• ISBN-10: 0-13-226416-1
• ISBN-13: 978-0-13-226416-7

Image processing, the use of computers to process pictures, has revolutionized the fields of medicine, space exploration, geology, and oceanography, and has become the hottest area in digital signal processing. This book provides a comprehensive introduction to the most popular image processing techniques used today, without getting bogged down in the complex mathematical presentations found in most image processing books and journals. KEY TOPICS: The book covers the hottes t topics in image proessing, including whole chapters on the processing of color images, image warping and morphing techniques, and image compression. The diskette, written in portable C code, provides a "hands-on" introduction to image processing techniques that can be incorporated into the user's applications. MARKET: For computer programmers and electrical engineers who need to enhance image processing applications.

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Downloads

As an aid to readers of A Simplified Approach to Image Processing: Classical and Modern Techniques in C, we are providing for download the software listed in the book in a compressed archive.

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Sample Content

Table of Contents

(NOTE: Each chapter ends with a 'For further study' section.)
1. Introduction.

What is image processing? Visual perception. Color representation. Image capture, representation and storage. Image output. The software.

2. Point Processes.
Arithmetic operations. XOR. Look-up tables. Histograms. Contrast Stretching. Intensity transforms.

3. Area Processes.
Convolutions. Blurring. Sharpening. Edge detection. Median filtering. Min/max filtering.

4. Geometric Processes.
Forward and inverse mapping. Interpolation. Scaling. Rotation. Translation. Mirroring.

5. Frame Processes.
Addition. Subtraction. And/or. Average.

6. Image Halftoning.
Introduction to halftoning. Patterning. Dithering. Error diffusion. Beyond bilevel output. Practical considerations when halftoning.

7. Image Transforms.
Introduction to the frequency domain. Discrete fourier transform. Filtering in the frequency domain. Discrete cosine transform.

8. Image Warping and Morphing.
Introduction to 2-dimensional morphing. Spatial transformations. Meshwarp algorithm. Field warping algorithm. Cross dissolve. Practical considerations when morphing.

9. Image Compression.
Introduction to image compression. Run-length encoding. Huffman coding. Modified Huffman coding. Modified READ. Limpel Ziv Welch algorithm. Arithmetic coding. JPEG. Other state-of-the-art image compression methods.

Appendix: Image Processing Resources.
Glossary.
Bibliography.
Index.

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