Video sources produce data at very high bit rates. In many applications, the available bandwidth is usually very limited.

The scanning format of a video signal is a major determinant of general picture quality. Specifically, it determines such aspects as stationary and dynamic resolution, motion portrayal, aliasing, scanning structure visibility, and flicker.

Digital images and video, acquired by still cameras, consumer camcorders, or even broadcast-quality video cameras, are usually degraded by some amount of blur and noise.

Digital representation of images is important for digital transmission and storage on differentmedia suchasmagnetic or laser disks.

Experts in every field of study depend on specialized tools. In the case of speech research and development, the dominant tools today are computer programs. In this article, we present an overview of key technical approaches and features that are prevalent today.

Speaker recognition is the process of automatically extracting personal identity information by analysis of spoken utterances.

Over the past several decades a need has arisen to enable humans to communicate with machines in order tocontrol their actions or toobtaininformation.

Text-to-speech synthesis has had a long history, one that can be traced back at least to Dudley’s “Voder”, developed at Bell Laboratories and demonstrated at the 1939 World’s Fair [1].

Digital speech coding is used in a wide variety of everyday applications that the ordinary person takes for granted, such as network telephony or telephone answering machines.

The characteristics of a speech signal that are exploited for various applications of speech signal processing to be discussed later in this section on speech processing (e.g., coding, recognition, etc.) arise from the properties and constraints of the human vocal apparatus.

In digital signal processing, manipulating of the signal is defined as an essentially mathematical procedure, while the AD and DA converters, the front end and the final stage devices of the processing, include analog factor/limitation.

With the overwhelming success of the compact disc (CD) in the consumer audio marketplace, the public’s notion of “high quality audio” has become synonymous with “compact disc quality”.

In order to more efficiently transmit or store high-quality audio signals, it is often desirable to reduce the amount of information required to represent them.

Typical audio signal classes are telephone speech, wideband speech, and wideband audio, all of which differ in bandwidth, dynamic range, and in listener expectation of offered quality. The quality of telephone-bandwidth speech is acceptable for telephony and for some videotelephony and video-conferencing services.

A coded signal differs in some respect from the original signal. One task in designing a coder is to minimize some measure of this difference under the constraints imposed by bit rate, complexity, or cost.

The idea of a lapped transform (LT) maintaining orthogonality and non-expansion of the samples was developed in the early 1980s at MIT by a group of researchers unhappy with the blocking artifacts so commonin traditional block transformcoding of images.

Time-frequency representations (TFR) combine the time-domain and frequency-domain representations intoasingle frameworktoobtainthe notionof time-frequency.

The interest in digital filter banks has grown dramatically over the last few years. Owing to the trend toward lower cost, higher speed microprocessors, digital solutions are becoming attractive for a wide variety of applications.

The methods of designing bases that we will employ draw on ideas first used in the construction of multirate filter banks. The ideaof suchsystems is totake aninput systemandsplit it intosubsequences using banks of filters.

In this chapter we consider a class of iterative restoration algorithms. If y is the observed noisy and blurred signal, D the operator describing the degradation system, x the input to the system, and n the noise added to the output signal, the input-output relation is described by [3, 51]