Editing False color (section)

===Density slicing===
[[File:Tasmania 27nov81.png|thumb|left|An image of [[Tasmania]] and surrounding waters using density slicing to show [[phytoplankton]] concentration. The ocean color as captured by the satellite image is mapped to seven colors: Yellow, orange and red indicate more phytoplankton, while light green, dark green, light blue and dark blue indicate less phytoplankton; land and clouds are depicted in different colors.]]
'''Density slicing''', a variation of pseudo color, divides an image into a few colored bands and is (among others) used in the analysis of [[remote sensing]] images.<ref>
{{cite book
 | title = Remote Sensing Digital Image Analysis: An Introduction
 | edition = 4th
 |author1=John Alan Richards |author2=Xiuping Jia|author2-link=Xiuping Jia | publisher = Birkhäuser
 | year = 2006
 | isbn = 9783540251286
 | pages = 102–104
 | url = https://books.google.com/books?id=xFg-99738poC&pg=PA102
 | access-date = 2015-07-26
 }}</ref> For density slicing the range of grayscale levels is divided into intervals, with each interval assigned to one of a few discrete colors – this is in contrast to pseudo color, which uses a continuous color scale.<ref>J. B. Campbell, "Introduction to Remote Sensing", 3rd ed., Taylor & Francis, p. 153</ref> For example, in a grayscale [[Thermography|thermal image]] the temperature values in the image can be split into bands of 2&nbsp;°C, and each band represented by one color – as a result the temperature of one spot in the thermograph can be easier acquired by the user, because the discernible differences between the discrete colors are greater than those of images with continuous grayscale or continuous pseudo color.
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