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1988 | Buch

Digital Pictures

Representation and Compression

verfasst von: Arun N. Netravali, Barry G. Haskell

Verlag: Springer US

Buchreihe : Applications of Communications Theory

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For thousands of years mankind has been creating pictures which attempt to portray real or imagined scenes as perceived by human vision. Cave drawings, paintings and photographs are able to stimulate the visual system and conjure up thoughts of faraway places, imagined situations or pleasant sensations. The art of motion picture creation has advanced to the point where viewers often undergo intense emotional experiences. On-the­ spot news coverage gives the impression of actually witnessing events as they unfold. Relatively recently, other forms of visual information have been invented which do not, in themselves, stimulate the eye. For example, vol­ tage variations in an electrical signal, as in television, can represent in analogous fashion the brightness variations in a picture. In this form the visual information can be stored on magnetic tape or transmitted over long distances, and, at least for engineering purposes, it is often much more use­ ful than other forms which do stimulate human vision. With the evolution of digital techniques for information processing, storage, and transmission, the need arises for digital representation of visual information, that is, the representation of images by a sequence of integer numbers (usually binary). In this form, computer processing and digital circuit techniques can be utilized which were undreamed of only a short time ago. Machine manipulation and interpretation of visual infor­ mation becomes possible. Sophisticated techniques can be employed for efficient storage of images. And processing methods can be used to significantly reduce the costs of picture transmission.

Inhaltsverzeichnis

Frontmatter
1. Numerical Representation of Visual Information
Abstract
The ability to see is one of the truly remarkable characteristics of living beings. It enables them to perceive and assimilate in a very short time an incredible amount of knowledge about the world around them. The scope and variety of that which can pass through the eye and be interpreted by the brain is nothing short of astounding. Mankind has increased this basic capability by inventing devices that can detect electromagnetic radiation at wavelengths far outside the range of normal vision and at energy levels orders of magnitude below what the eye is able to perceive by itself. By the use of X-rays or sound waves it is possible to “see” inside objects and into places that have been invisible to living beings since the dawn of creation. Ultra-fast photography can stop a speeding bullet or freeze a flying humming bird’s wing.
Arun N. Netravali, Barry G. Haskell
2. Common Picture Communication Systems
Abstract
In this chapter we describe the operation of several picture communication systems in order to understand better the fundamentals and applications of image coding methods to be described later. We begin with monochrome television, followed by the three major color TV systems, NTSC, PAL and SECAM.
Arun N. Netravali, Barry G. Haskell
3. Redundancy-Statistics-Models
Abstract
In the first two chapters we discussed primarily how to represent visual information by a finite amount of digital data, or in the case of time-varying images, by a finite data rate. However, the data produced by these techniques normally contains a considerable amount of superfluous information that can be removed by methods to be discussed here and in later chapters.
Arun N. Netravali, Barry G. Haskell
4. Visual Psychophysics
Abstract
One of the most important objectives in the design of visual communication systems is that it only represent, transmit and display that information which the human eye can see. To transmit and display characteristics of images that a human observer cannot perceive is a waste of channel resources and display media. We must understand therefore how we can represent pictures economically and transmit them with the minimum accuracy required by the human eye. In this chapter we study those properties of human vision that are helpful in evaluating the quality of a coded picture and which thereby help us in optimizing the coder to achieve the lowest transmission rate for a given picture quality. In a practical communication system, the goal of making the reproduced picture identical to the original is beset with many difficulties and is not realistic. Systematic distortions occur, for example, in representing a live scene by a television system. The contrast ratio in a natural sunlit scene (the ratio of the highest to the lowest luminance) can frequently be 200:1 or greater, whereas for most television systems, a contrast ratio of even 50:1 is difficult to obtain. Also, color television systems use three primary colors to reproduce the approximate chromaticities of the original scene (i.e. metameric matches). Television does not reproduce a scene with the same spectral distribution as the original.
Arun N. Netravali, Barry G. Haskell
5. Basic Compression Techniques
Abstract
We have so far described the nature and properties of picture signals such as the television signal and the facsimile signal. In particular, we considered statistical properties of pictures and the properties of the human viewer that are relevant to the coding problem. In this chapter we will describe many of the basic coding approaches that have been successfully used for digital picture communication. Emphasis will be on general principles, and how they are related or derived from the picture statistics and psychophysics of vision. We start with a classification of coding schemes and then describe them in some detail outlining procedures for optimizing their parameters.
Arun N. Netravali, Barry G. Haskell
6. Examples of Codec Designs
Abstract
In this chapter we describe several image codec designs in some detail. Our purpose is not to present the current state of the art, for that changes almost on a daily basis. Rather, we wish to show how the basic principles discussed in previous chapters might be applied in an interrelated way to practical systems. Some applications require a simple codec without a high degree of data compression. In other cases we need a low bit-rate because of expensive transmission channels, and codec cost is less of a consideration. In still other situations we want very high picture quality, with less concern about low complexity and compression capabilities. The techniques described in this chapter cover a range of complexity, picture quality and data compression in order to assist in the making of sound engineering decisions when designing image communication systems. However, some of the implementations also contain a certain amount of ad hoc procedures that can only be optimized by experimentation.
Arun N. Netravali, Barry G. Haskell
7. Postscript
Abstract
In order to transmit video information at the minimum bit rate for a given quality of reproduction it is necessary to exploit our understanding of many branches of science. Ideally one should have an appreciation of vision, signal theory, display devices, and so on. As engineers we are concerned with complex stimuli, their perception, as well as the final utilization of the perceived information. Knowledge of these is often unavailable or sketchy, forcing us to design encoders based on a relatively primitive understanding of the problem. The ultimate limits of bit-rate compression will only be approached, we believe, as our knowledge of stimuli, perception and utilization increases.
Arun N. Netravali, Barry G. Haskell
Backmatter
Metadaten
Titel
Digital Pictures
verfasst von
Arun N. Netravali
Barry G. Haskell
Copyright-Jahr
1988
Verlag
Springer US
Electronic ISBN
978-1-4684-1294-9
Print ISBN
978-1-4684-1296-3
DOI
https://doi.org/10.1007/978-1-4684-1294-9