Computer)Graphics Graphics)Formats))sanja/ComputerGraphics/L02...Computer)Graphics)...

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Computer Graphics Graphics Formats Aleksandra Pizurica L02_2 Overview •Graphic formats Vector graphics Raster graphics • Color percepDon and reproducDon TrisDmulus theory of color percepDon True color images Indexed color images Graphic formats Vector and Raster Graphics • There are two main types of computer images Raster images • Each image point separately stored Vector images • Image consists of objects • Objects are represented by their contours • Each of these formats has certain advantages and disadvantages and they are generally used for different purposes L02_4 Vector graphics Represented in terms of verDces (points) and lines. Lines can be straight or curved; Generated mathemaDcally Ideal for “simple” images with precise contours (cartoons, logo’s,…) For displaying on CathodeRay Tube (CRT) screen, a vector generator converts the digital coordinates to analog voltages for beam deflecDon L02_5 Fig. 1.4 from book FvDFH Ideal line drawing Vector scan Represented in terms of elementary picture elements: pixels Well suited for images with a variety of intensity levels, such as digital photographs and other “realisDc” images Commonly referred to as bitmap (BMP) even though bitmap strictly speaking applies only to binary systems Raster graphics L02_6 Ideal line drawing Raster scan with filled primiDves Fig. 1.4 from book FvDFH

Transcript of Computer)Graphics Graphics)Formats))sanja/ComputerGraphics/L02...Computer)Graphics)...

Page 1: Computer)Graphics Graphics)Formats))sanja/ComputerGraphics/L02...Computer)Graphics) Graphics)Formats)) AleksandraPizurica)))) L02_2 Overview •Graphic)formats)!)Vector)graphics)!)Raster)graphics)

Computer  Graphics  Graphics  Formats    

Aleksandra  Pizurica  

 

   

L02_2  

Overview  

• Graphic  formats  §   Vector  graphics  §   Raster  graphics  

•   Color  percepDon  and  reproducDon  §   TrisDmulus  theory  of  color  percepDon  §   True  color  images  §   Indexed  color  images  

Graphic  formats  

Vector  and  Raster  Graphics  

•  There  are  two  main  types  of  computer  images  §   Raster  images  

•   Each  image  point  separately  stored  §   Vector  images  

•   Image  consists  of  objects  •   Objects  are  represented  by  their  contours  

•  Each  of  these  formats  has  certain  advantages  and  disadvantages  and  they  are  generally  used  for  different  purposes  

L02_4

Vector  graphics  

•  Represented  in  terms  of  verDces  (points)  and  lines.  

•  Lines  can  be  straight  or  curved;  Generated  mathemaDcally  

•  Ideal  for  “simple”  images  with  precise  contours  (cartoons,  logo’s,…)  

•  For  displaying  on  Cathode-­‐Ray  Tube  (CRT)  screen,  a  vector  generator  converts  the  digital  coordinates  to  analog  voltages  for  beam  deflecDon  

L02_5 Fig.  1.4  from  book  FvDFH  

Ideal  line  drawing   Vector  scan   Raster  outline  

•  Represented  in  terms  of  elementary  picture  elements:  pixels  

•  Well  suited  for  images  with  a  variety  of  intensity  levels,  such  as  digital  photographs  and  other  “realisDc”  images  

•  Commonly  referred  to  as  bitmap  (BMP)  even  though  bitmap  strictly  speaking  applies  only  to  binary  systems  

Raster  graphics  

L02_6

Ideal  line  drawing   Raster  scan  with  filled  primiDves  

Fig.  1.4  from  book  FvDFH  

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An  example  of  a  raster  image  

Illustration from computer graphics course of Patrick Bergmans

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Architecture  of  a  raster  display  

Fig.  1.2  from  book  FvDFH  

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The  raster  is  stored  as  a  matrix  of  pixels  represenDng  the  screen  area.  The  image  is  scanned  sequenDally  (video  controller)  one  line  at  a  Dme.  At  each  pixel,  the  beam  intensity  is  adjusted  according  to  pixel  intensity.  

Frame  Buffer  Refresh  

Refresh  rate  typically  60-­‐75Hz  Fig.  1.3  from  book  FvDFH  

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Vector  Versus  Raster  Systems  

•  Advantages  of  raster  systems  §   Richer  textural  and  pagern  representaDon    § Cheaper  (repeDDve  regular  scanning  compared  to  complex  random  scan  of  vector  systems)  

•  Advantage  of  vector  systems  §   No  jaggies  §   Scales  up  arbitrarily  retaining  perfectly  smooth  lines  §   Easier  real-­‐Dme  manipulaDon  

Example  from  Wikipedia  

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Color  percepDon  and  reproducDon  

Color  PercepDon  (1)  

•  Color  as  such  does  not  exist  in  nature!  §   (Colored)  light  consists  of  electromagneDc  waves  of  different  frequencies  (or  wavelengths)    

•  Color  percepDon  is  three-­‐dimensional    (3D)  §   We  have  three  types  of  “sensors”  in  the  eye,  which  are  sensiDve  to  different  parts  of  the  spectrum  (TrisDmulus  theory  of  color)  

•  All  color  representaDons  are  hence  3D  §   AddiDve  (RGB)  ;  red-­‐green-­‐blue  §   SubtracDve  (CMY)  ;  cyan-­‐magenta-­‐yellow  §   Other  (HSV,  Luv,  Lab)  

•  We  limit  ourselves  to  RGB  representaDon  

L02_12

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Color  PercepDon  (2)  

L02_13

Spectral-­‐response  funcDons  of  the  three  types  of  cones  in  the  human  reDna.  

Fig.  13.18  from  book  FvDFH    

Color  PercepDon  (3)  

•  Natural  white  light  consists  of  an  conDnuous  and  uniform  spectrum  of  EM  waves,  visible  from  violet  to  red  (rainbouw)  

Ultra  violet   infrared  

wavelength  400  nm   750  nm  

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Color  PercepDon  (4)  

•  Color  percepDon  depends  only  on  how  the  light  acDvated  each  of  the  three  sensors  (Red,  Green  and  Blue)  

wavelength  

wavelength  

Note:  Spectral  responses  here  are  only  schemaDcal  (true  ones  on  slide  #13)    

Illustration from computer graphics course of Patrick Bergmans

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Color  PercepDon  (5)  

•  Two  totally  different  spectra  can  be  perceived  as  the  same  color  

wavelength  

wavelength  Illustration from computer graphics course of Patrick Bergmans

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Color  PercepDon  (6)  

•  Two  totally  different  spectra  can  be  perceived  as  the  same  color  

•  To  reproduce  arDficially  (the  impression  of)  a  color,  it  is  sufficient  to  generate  the  same  sensor  sDmuli  

•  This  is  best  done  with  light  sources  with  wavelengths  that  are  close  to  the  maximum  sensiDvity  of  the  sensors,  hence  Red,  Green,  Blue  à  called  R,  G,  B  primaries  

•  This  process  is  called  addiDve  color  synthesis  §   By  mixing  R,  G,  B  primaries  in  the  right  proporDons,  we  can  create  impressions  of  all  colors  

L02_17

Color images (1)

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Color  images  (2)  

•  One  bit  per  color  (0/1)  –  3  bits/pixel  

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Color  images  (3)  

•  With  8  bits  per  color  channel  à  24  bits  per  pixel  

•  In  this  way  we  can  theoreDcally  represent  16.777.216  different  colors  

•  Human  eye  can  differenDate  “only”  several  hundreds  of  thousands  of  colors  

•  The  24-­‐bit  representaDon  is  in  principle  inefficient  

•  However,  much  simpler  than  the  “opDmal”  one  

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Color  images  (4)  

•  Eight  bits  per  color  (0-­‐255).  24  bits/pixel  

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Indexed  color  images  

•  24  bits  is  too  much  for  some  applicaDons  §   Especially  when  the  image  contains  only  a  limited  number  of  colors  (e.g.,  cartoon  or  logo)  

•  SoluDon:  instead  of  represenDng  a  color  with  24  bits  give  as  input  the  color  “index”,  i.e.,  the  number  of  this  color  

§   How  many  colors  need  to  be  displayed  at  a  Dme?  N  §   How  many  bits  are  needed  to  represent  this  number?  n  =  log2(N)    §   For  N=256,  n=8  

•  Most  common  are  color  palletes  with  4,  16  and  256  colors.  The  color  index  of  each  pixel  is  then  represented  with  2,  4  and  8  bits,  respecDvely.  

L02_22

Indexed  color  images  

color  2  (20,150,200)  

color  3  (0,200,150)  

color  253  (200,0,20)  

color  1  (120,60,80)  

color  0  (200,100,0)  

color  254  (255,255,255)  

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Indexed  color  images  

•  Color-­‐look-­‐up  (CLT)  table  gives  the  relaDonschip  between  the  color  index  and  the  true  color  

RED GREEN BLUE

0 200 100 01 120 60 802 20 150 2003 0 200 1504 50 100 150… … … …… … … …253 200 0 20254 255 255 255255 0 0 200

24  bits  

N  =  2

n    posiDon

s   color  nr.  0  color  nr.  1  color  nr.  2  

etc.  

     color  nr.  255        color  nr.  254        color  nr.  253  

L02_24

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Problems  with  CLT  

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•  It  can  be  difficult  to  exchange  raw  image  data  and/or  color  map  tables  between  different  image  files  (intermediate  mapping  needed).    

•  If  the  original  color  palege  for  a  given  indexed  image  is  lost,  it  can  be  nearly  impossible  to  restore  it.  

A  typical  indexed  256-­‐color  image  and  a  result  of  restoring  it  with  a  wrong  color  palege  [hgp://en.wikipedia.org/wiki/

Indexed_color]  

Summary  

•  Vector  and  raster  graphics  have  each  their  advantages  in  certain  applicaDons.  

•  By  mixing  R,  G  and  B  primaries  in  the  right  proporDons  all  colors  can  be  reproduced.  

•  Indexed  color  paleges  interesDng  in  many  pracDcal  applicaDons,  especially  for  ‘cartoon-­‐like’  images  (with  piece-­‐wise  uniform  colors)  and  logos.    

 

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