Image and Video Compression

Book description

Image and video signals require large transmission bandwidth and storage, leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus, efficient image and video compression algorithms play a significant role in the storage and transmission of data.

Image and Video Compression: Fundamentals, Techniques, and Applications explains the major techniques for image and video compression and demonstrates their practical implementation using MATLAB® programs. Designed for students, researchers, and practicing engineers, the book presents both basic principles and real practical applications.

In an accessible way, the book covers basic schemes for image and video compression, including lossless techniques and wavelet- and vector quantization-based image compression and digital video compression. The MATLAB programs enable readers to gain hands-on experience with the techniques. The authors provide quality metrics used to evaluate the performance of the compression algorithms. They also introduce the modern technique of compressed sensing, which retains the most important part of the signal while it is being sensed.

Table of contents

  1. Front Cover (1/2)
  2. Front Cover (2/2)
  3. Contents (1/2)
  4. Contents (2/2)
  5. Preface
  6. Authors
  7. Chapter 1: Introduction to Image Compression
  8. Chapter 2: Lossless Image Compression (1/4)
  9. Chapter 2: Lossless Image Compression (2/4)
  10. Chapter 2: Lossless Image Compression (3/4)
  11. Chapter 2: Lossless Image Compression (4/4)
  12. Chapter 3: Image Transforms (1/8)
  13. Chapter 3: Image Transforms (2/8)
  14. Chapter 3: Image Transforms (3/8)
  15. Chapter 3: Image Transforms (4/8)
  16. Chapter 3: Image Transforms (5/8)
  17. Chapter 3: Image Transforms (6/8)
  18. Chapter 3: Image Transforms (7/8)
  19. Chapter 3: Image Transforms (8/8)
  20. Chapter 4: Wavelet-Based Image Compression (1/4)
  21. Chapter 4: Wavelet-Based Image Compression (2/4)
  22. Chapter 4: Wavelet-Based Image Compression (3/4)
  23. Chapter 4: Wavelet-Based Image Compression (4/4)
  24. Chapter 5: Image Compression Using Vector Quantization (1/6)
  25. Chapter 5: Image Compression Using Vector Quantization (2/6)
  26. Chapter 5: Image Compression Using Vector Quantization (3/6)
  27. Chapter 5: Image Compression Using Vector Quantization (4/6)
  28. Chapter 5: Image Compression Using Vector Quantization (5/6)
  29. Chapter 5: Image Compression Using Vector Quantization (6/6)
  30. Chapter 6: Digital Video Compression (1/6)
  31. Chapter 6: Digital Video Compression (2/6)
  32. Chapter 6: Digital Video Compression (3/6)
  33. Chapter 6: Digital Video Compression (4/6)
  34. Chapter 6: Digital Video Compression (5/6)
  35. Chapter 6: Digital Video Compression (6/6)
  36. Chapter 7: Image Quality Assessment (1/4)
  37. Chapter 7: Image Quality Assessment (2/4)
  38. Chapter 7: Image Quality Assessment (3/4)
  39. Chapter 7: Image Quality Assessment (4/4)
  40. Chapter 8: Compressive Sensing (1/11)
  41. Chapter 8: Compressive Sensing (2/11)
  42. Chapter 8: Compressive Sensing (3/11)
  43. Chapter 8: Compressive Sensing (4/11)
  44. Chapter 8: Compressive Sensing (5/11)
  45. Chapter 8: Compressive Sensing (6/11)
  46. Chapter 8: Compressive Sensing (7/11)
  47. Chapter 8: Compressive Sensing (8/11)
  48. Chapter 8: Compressive Sensing (9/11)
  49. Chapter 8: Compressive Sensing (10/11)
  50. Chapter 8: Compressive Sensing (11/11)
  51. Back Cover

Product information

  • Title: Image and Video Compression
  • Author(s): Madhuri A. Joshi, Mehul S. Raval, Yogesh H. Dandawate, Kalyani R. Joshi, Shilpa P. Metkar
  • Release date: November 2014
  • Publisher(s): CRC Press
  • ISBN: 9781482228236