0 CHECKOUT

Still Image and Video Compression with MATLAB

  • ID: 1790643
  • December 2010
  • 428 Pages
  • John Wiley and Sons Ltd
1 of 4

The Most Comprehensive Coverage of the Theory and Practice of Image and Video Compression

This authoritative text enables readers to grasp the basic principles of still image and video compression methods as well as the current and popular compression standards, such as JPEG, MPEG, and Advanced Video Coding (AVC). Written in clear language and with minimal mathematical derivations, it allows readers to gain practical experience in simulating actual compression systems via the globally popular MATLAB software platform.

The book first introduces qualitatively the plethora of image compression methods available followed by image acquisition techniques, illustrating the design of uniform and non–uniform quantizers. Next, various image transforms such as the discrete cosine (dct) and discrete wavelet (dwt) are explained. Predictive coding a core ingredient in various compression standards is reviewed, along with lossless compression methods. Then follow chapters on still image compression schemes using DCT and wavelets (where JPEG and JPEG2000 standards for still image compression are described) and video coding principles. Finally, the book explains video compression READ MORE >

Note: Product cover images may vary from those shown
2 of 4

Preface.

1 Introduction.

1.1 What is Source Coding?

1.2 Why is Compression Necessary?

1.3 Image and Video Compression Techniques.

1.4 Video Compression Standards.

1.5 Organization of the Book.

1.6 Summary.

References.

2 Image Acquisition.

2.1 Introduction.

2.2 Sampling a Continuous Image.

2.3 Image Quantization.

2.4 Color Image Representation.

2.5 Summary.

References.

Problems.

3 Image Transforms.

3.1 Introduction.

3.2 Unitary Transforms.

3.3 Karhunen Loeve Transform.

3.4 Properties of Unitary Transforms.

3.5 Summary.

References.

Problems.

4 Discrete Wavelet Transform.

4.1 Introduction.

4.2 Continuous Wavelet Transform.

4.3 Wavelet Series.

4.4 Discrete Wavelet Transform.

4.5 Efficient Implementation of 1D DWT.

4.6 Scaling and Wavelet Filters.

4.7 Two–Dimensional DWT.

4.8 Energy Compaction Property.

4.9 Integer or Reversible Wavelet.

4.10 Summary.

References.

Problems.

5 Lossless Coding.

5.1 Introduction.

5.2 Information Theory.

5.3 Huffman Coding.

5.4 Arithmetic Coding.

5.5 Golomb Rice Coding.

5.6 Run Length Coding.

5.7 Summary.

References.

Problems.

6 Predictive Coding.

6.1 Introduction.

6.2 Design of a DPCM.

6.3 Adaptive DPCM.

6.4 Summary.

References.

Problems.

7 Image Compression in the Transform Domain.

7.1 Introduction.

7.2 Basic Idea Behind Transform Coding.

7.3 Coding Gain of a Transform Coder.

7.4 JPEG Compression.

7.5 Compression of Color Images.

7.6 Blocking Artifact.

7.7 Variable Block Size DCT Coding.

7.8 Summary.

References.

Problems.

8 Image Compression in the Wavelet Domain.

8.1 Introduction.

8.2 Design of a DWT Coder.

8.3 Zero–Tree Coding.

8.4 JPEG2000.

8.5 Digital Cinema.

8.6 Summary.

References.

Problems.

9 Basics of Video Compression.

9.1 Introduction.

9.2 Video Coding.

9.3 Stereo Image Compression.

9.4 Summary.

References.

Problems.

10 Video Compression Standards.

10.1 Introduction.

10.2 MPEG–1 and MPEG–2 Standards.

10.3 MPEG–4.

10.4 H.264.

10.5 Summary.

References.

Problems.

Index.

Note: Product cover images may vary from those shown
3 of 4

K.S. Thyagarajan is Chief Scientist at Micro USA, Inc., where he has developed an extensive suite of image processing, detection, and classification algorithms for the detection of very low contrast targets underwater in littoral waters and open oceans. He is an Emeritus Professor in the Department of Electrical and Computer Engineering at San Diego State University, and has extensive academic and industrial experience in researching and developing video compression systems. Dr. Thyagarajan's expertise lies in signal, image processing, image and video compression, pattern recognition, and communications. He holds several patents in video compression.

Note: Product cover images may vary from those shown
4 of 4
Note: Product cover images may vary from those shown

PURCHASING OPTIONS

HAVE A QUESTION?

EMAIL US VIEW FAQs

RELATED PRODUCTS from Db

Our Clients

  • Symantec Corporation
  • Genesys Telecommunications Laboratories, Inc.
  • Adobe Systems Incorporated
  • Ir Prognosis
  • NCR Corporation
  • Oracle Corporation