Color Spaces and Color depth




Color Spaces


Color spaces are different types of color modes, used in image processing .
 it  is a specific organization of colors.  



Some of the common color spaces are:

  • RGB
  • HSV
  • CMY’K
  • Y’UV
  • YIQ
  • Y’CbCr



RGB is the most widely used color space especially in computer vision field  so we will explain it in this article .




Color model RGB


RGB is used in your TV and computer screens, and hence on web pages
each color image is actually formed of three different images. Red image, Blue image, and black image.


[ R=red -- G=green -- B=blue ] (source)



And every color have scale or range from 0 to 255  .
So if we have  image like this(only black image) :

That’s mean the value of red color in this image is 0 and the value of green color in this image is 0 and the value of green color is also 0 .
 rgb = (0 , 0 ,0)  --   so the result was a black image .

 *********************

And if the image is like this (only red image)
That’s mean rgb = (255 , 0 ,0)


 *********************


And if the image is like this (only green image)
That’s mean rgb = (0 , 255 ,0)


And the blue image is the same concept with rgb = (0 , 0 ,255) and the white image is the same concept with rgb = (255 , 255 ,255)

Therefore, based on the previous article we conclude that each pixel in the picture has its own characteristics and color and it is now possible to represent this color using RGB System



finally, the color image matrix = red matrix + blue matrix + green matrix




Gray scale image

greyscale image is one in which the value of each pixel is a single sample representing only an amount of light, also, it carries only intensity information. Images of this sort, also known as black-and-white or gray monochrome.




A normal gray scale image can be defined by only one matrix
RGB images are composed of three independent channels for red, green and blue but grayscale images have only one channel   with only two colors: black and white (also called bilevel or binary images)


256 different intensity values for each primary color(source)







Color depth


Color depth also known as bit depth, is the number of bits used to indicate the color of a single pixel.

bit depth specifies the number of bits used for each color component of a single pixel.

A bit is the unit of storage in a digital computer.  There are only two numeric values that can be stored in a single bit: 0 and 1.  A ’0’ bit represents the number zero, and a ’1’ bit represents the number one. 


 

For example, the number 100101 in binary represents the number 37 in decimal (decimal is the number system that we use in everyday life, while binary is the number system used internally by computers). 

This image show how to convert from bits to decimal


  

To represent numbers greater than one in binary system, we need to use multiple bits in combination. For a given number of bits, say (8-bit), there is a smallest number that can be represented, and a largest number that can be represented.


  The smallest 8-bit binary number (used Alot for representing colors) is 00000000, which represents zero, while the largest is 11111111, which represents 255


(256 different intensity values for every channel )


So if we increase the color depth that’s mean the pixel will have more levels of colors to every channel and this enhance the image accuracy .






 

Comparison: same image on five different color depths (bits)


 

The following table illustrates different image types in terms of bits (bit depth), total colors available, and common names.





I hope this article has been reported to you - I have tried hard to shorten it without a work flaw in understanding the basics as much as possible.
Be free to contact via my email any time
Thanks.












References /





https://en.wikipedia.org/wiki/Color_depth











Comments

Popular posts from this blog

What is computer vision?

Pixels With Coordinate System and Resolution