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Image Data Formats and Color Representation

  • Alejandro C. Frery
  • Talita Perciano
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

This chapter starts with a brief introduction about color representation. The nature of the light reflected by an object, along with its optical characteristics and the human perception, is responsible for its appearance. The light is characterized by the attributes of intensity, radiance, luminance, and brightness. Colors are electromagnetic waves described by their wavelength and they are considered to be formed from different combinations of the primary colors red, green, and blue. The color depth measures the amount of color information available to display or print each pixel of a digital image. The higher the color depth, the more accurate the color representation. The most used color models are RGB, CMYK, and HSV. The first one is usually used for representing colors in electronic devices as TV and computer monitors, scanners, and digital cameras. The CMYK space is usually used by printers and photocopiers, while the HSV model is used in artificial vision systems. The two main classes used to store images, vector, and raster, are also presented in this chapter. In a vector format the image is described by geometrical primitives, while in a raster format it is described by a matrix of values. Some common vector formats are PDF, PostScript and SVG, and the most used raster formats are TIFF, JPEG, PNG, BMP, and PBM. Procedures on how to read and write graphics in the formats presented using R are presented in the next chapter.

Keywords

Color Space Joint Photographic Expert Group Color Representation Portable Document Format Color Depth 
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

© Alejandro C. Frery 2013

Authors and Affiliations

  1. 1.Instituto de ComputaçãoUniversidade Federal de AlagoasMaceióBrazil
  2. 2.Instituto de Matemática e EstatísticaUniversidade de São PauloSão PauloBrazil

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