HSV Color Space

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Standing for hue, saturation, and value, HSV seeks to explain the relationship between colors.
Relationship between Hue, Saturation and Color
HSV (Hue-Saturation-Value) is a Color model that specifies colors based on the dimensions of color most intuitive to human cognition.

Hue

According to the ESRI dictionary [1] Hue is the dominant wavelength of a color, by which it can be distinguished as red, green, yellow, blue, and so forth. [2] When you ask the question, "What color is that?" you are referring to its hue. [3] Hue is determined by the length of the light wave, only a few of which can be detected by the human eye. Data of different categories are represented by hue, thus in cartography, hue is used to represent qualitative data. [4] Hue cannot be used for numerical or ordered data because there is no order to color. Hue is essential in cartography to improve a map by using the visual symbols and data to tell the story.

Saturation (Chroma)

Saturation refers to the purity or intensity of a color and is related to how much gray is mixed into the color. Colors with high saturation have very little gray mixed in, while colors with low saturation have a lot of gray. More saturated colors are more intense or vivid in appearance.

Saturation is used along with lightness (value) and hue to determine an exact color. As such, these three elements form the structure for various color models. Saturation does not affect lightness or hue (light green, dark red, etc.), but it can make a color appear more vivid or dull. A saturated orange, for example, may appear much like the shade of orange on a tangerine peel, whereas an unsaturated orange appears shaded by gray. As a color’s lightness (value) decreases or becomes darker, the range of saturation decreases.

Although not as immediately apparent as hue or lightness, saturation can make certain colors stand out on a map and is therefore important to utilize. Saturation can be used to make otherwise unseen features come to the viewer’s attention. [5]

Saturation can be used to make otherwise unseen features come to the viewer’s attention. [6]

Value (Lightness)

Value is the lightness or darkness of a color. It can also be defined as the brightness of a color or how much light it reflects.[7] Different color models have different names for this property such as Lightness or Value but both represent the same idea. The color white has the highest amount of lightness and the color black has the lowest amount of lightness, so if one wants to increase the lightness of a color, add white, and the reverse if one wants to decrease the lightness of a color, add black. In terms of a spectral definition of color, lightness or value describes the overall intensity or strength of the light.[8] This results in colors with higher intensities of light to be lighter such as light blue, and those with lower intensities of light to be darker such as royal blue.

Tristimulus Theory

Combinations of Red, Green and Blue can make up every color.

The Tristimulus Theory states that because the human eye only has three kinds of color sensors (called cones) responsive to visible light, all colors can be represented by a combination of just three signals[9]. The three cones are named Long, Middle and Short, because of the wavelengths of light that they are most responsive to[10]. The three cones correspond with Red(575nm), Green(535nm), and Blue(445nm), respectively[11].

Use in Cartography

High resolution airborne magnetic and gamma-ray spectrometric data are better portrayed in pixel-image maps. The color images on these maps are constructed by converting images in the RGB color model to the HSV color model.

References

  1. http://en.wikipedia.org/wiki/Hue
  2. http://support.esri.com/es/knowledgebase/GISDictionary/term/hue, GIS Dictionary. Sept. 09, 2012
  3. Farlex, http://www.thefreedictionary.com/Hue, The Free Dictionary. Sept. 09, 2012
  4. Dursteler, Juan. "Color guidelines." The digital magazine of InfoVis.net. 16 October 2006. Web. 10 September 2012
  5. "Color Principles - Hue, Saturation, and Value." Scientific Visualization. NC State University College of Education - Graphic Communications Program; NC State Department of Public Instruction, 08 May 2000. Web. 10 Sep 2011.
  6. Brewer, Cynthia. Designing Better Maps: A Guide for GIS Users. Redlands, CA: ESRI Press, 2005. 97. Print.
  7. http://support.esri.com/en/knowledgebase/GISDictionary/term/value, GIS Dictionary. Sept. 09, 2012
  8. http://www.ncsu.edu/scivis/lessons/colormodels/color_models2.html#secondary, North Carolina State University. Sept. 09, 2012
  9. Understanding Color. (2016). Willamette.edu. Retrieved 12 September 2016, from https://www.willamette.edu/~gorr/classes/GeneralGraphics/Color/tristimulus.htm
  10. TriStimulus. (2016). Colorbasics.com. Retrieved 12 September 2016, from http://www.colorbasics.com/Tristimulus/
  11. Understanding Color. (2016). Willamette.edu. Retrieved 12 September 2016, from https://www.willamette.edu/~gorr/classes/GeneralGraphics/Color/tristimulus.htm