Principles of Digital Image Compression

  • Weidong Kou
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 333)


The word “image”has many meanings for us. What is an image? From Webster’s Encyclopedic Unabridged Dictionary of the English Language, we know that an image is a representation of a person, animal, or thing. Technically speaking, however an image is a two-dimensional signal perceived by the human visual system. Moving pictures such as we see in television, on movies, are a sequence of images. When an image is digitized, it becomes a digital image. A digital image is an array of a number of picture elements called pixels. Each pixel is represented by a real number or a set of real numbers in limited number of bits. Based on the accuracy of the representation, we can classify images into three categories, black and white images, gray scale images, and color images. The characteristics of each type of images are as follows:
  • For black and white images, each pixel is represented by one bit. These images are sometimes referred to as bi-level, binary, or bi-tonal images.

  • For gray scale images, each pixel is represented by a luminance (or intensity) level. For pictorial images, typical gray scale images are represented by 256 gray levels, or 8 bits. For document images, 4–7 bits are usually sufficient.

  • Color images have multiple components. Each pixel of a color image can be represented by luminance and chrominance components. For instance, the NTSC (National Television Systems Committee) transmission system uses the luminance Y, and two chrominances I and Q to represent color. The CCITT H.261 and MPEG standards use the luminance Y and two chrominances C B and C R to represent color.


Compression Ratio Image Compression Document Image Gray Scale Image Compression Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1995

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  • Weidong Kou

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