Compression

"A wonderful treasure chest of information; spanning a wide range of data compression methods, from simple text compression methods to the use of wavelets in image compression. It is unusual for a text on compression to cover the field so completely." – ACM Computing Reviews.

"A wonderful treasure chest of information; spanning a wide range of data compression methods, from simple test compression methods to the use of wavelets in image compression. It is unusual for a text on compression to cover the field so completely." – ACM Computing Reviews

Compressing data is an option naturally selected when faced with problems of high costs or restricted space. Written by a renowned expert in the field, this book offers readers a succinct, reader-friendly foundation to the chief approaches, methods and techniques currently employed in the field of data compression.

Computer Speech is an introduction to multimedia speech applications and is suitable for nonspecialists. It treats such contemporary subjects as automatic speech recognition and speaker verification for banking by computer and privileged (medical, military, diplomatic) information and control access. The book also focusses on speech and audio compression for mobile communication and the Internet.

viii • The second new chapter, Chapter 6, discusses video compression. The chapter opens with a general description of CRT operation and basic analog and digital video concepts. It continues with a general discussion of video compression, and it concludes with a description of MPEG-1 and H.261. • Audio compression is the topic of the third new chapter, Chapter 7. The first topic in this chapter is the properties of the human audible system and how they can be exploited to achieve lossy audio compression. A discussion of a few simple audio compression methods follows, and the chapter concludes with a description of the three audio layers of MPEG-1, including the very popular mp3 format. Other new material consists of the following: • Conditional image RLE (Section 1.4.2). • Scalar quantization (Section 1.6). • The QM coder used in JPEG, JPEG 2000, and JBIG is now included in Sec­ tion 2.16. • Context-tree weighting is discussed in Section 2.19. Its extension to lossless image compression is the topic of Section 4.24. • Section 3.4 discusses a sliding buffer method called repetition times. • The troublesome issue of patents is now also included (Section 3.25). • The relatively unknown Gray codes are discussed in Section 4.2.1, in connection with image compression. • Section 4.3 discusses intuitive methods for image compression, such as subs- pling and vector quantization.

Digital image business applications are expanding rapidly, driven by recent advances in the technology and breakthroughs in the price and performance of hardware and firmware. This ever increasing need for the storage and transmission of images has in turn driven the technology of image compression: image data rate reduction to save storage space and reduce transmission rate requirements.

The book presents compression techniques for digital video stream, describing their design using various image transforms, such as discrete cosine transform (DCT), discrete wavelet transform (DWT), and singular value decomposition (SVD). It first discusses the basic requirements and applications of video compression techniques. The book then addresses video compression using DCT as well as the hybrid compression technique, designed and implemented using DCT, DWT and SVD, demonstrating the simulation results for both. Lastly, it proposes future research directions in the field.

Video technology promises to be the key for the transmission of motion video. A number of video compression techniques and standards have been introduced in the past few years, particularly the MPEG-1 and MPEG-2 for interactive multimedia and for digital NTSC and HDTV applications, and H.2611H.263 for video telecommunications. These techniques use motion estimation techniques to reduce the amount of data that is stored and transmitted for each frame.