Notes060709

Notes060709 - Honors 208W Fall 2011 Picture of Marilyn...

Info iconThis preview shows pages 1–8. Sign up to view the full content.

View Full Document Right Arrow Icon
Honors 208W Fall 2011 Histograms, Color Channels, and some Editing Techniques using GIMP Picture of Marilyn Monroe In Different Channels - Original from http://www.trojanhorseantiques.com/MMPhotoRedHeadshot.jpg
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Notes © 2005-2011 : Evan Golub (egolub@acm.org) Histograms • A histogram is a vertical bar graph with no spaces between the bar positions . • Using raw values, you might have some bars whose true height exceeds the height of the display window, so you might scale the histogram in some way so that the full height of the histogram’s space is utilized by the bar with the largest value. – Scaling can be linear, in which cane the largest value is used to mean “100% height” and the height of the other bars is based on the ratio of their value to that largest value. – It can also be logarithmic, in which case a log is selected that will allow the log largest value to mean “100% height” and the height of the other bars is based on taking that log of their values too.
Background image of page 2
Notes © 2005-2011 : Evan Golub (egolub@acm.org)
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Notes © 2005-2011 : Evan Golub (egolub@acm.org) Histograms: Lunar Example Linear Scaling Logarithmic Scaling
Background image of page 4
Notes © 2005-2011 : Evan Golub (egolub@acm.org) Histograms: Snow Example Logarithmic Scaling Linear Scaling
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Notes © 2005-2011 : Evan Golub (egolub@acm.org) Building a Histogram about an Image • To build a histogram displaying information about an image, we need to look at each pixel or the image, and “count” something. • For luminance, we can count how many pixels there are with each possible luminance level. – In a typical 24-bit RGB image, we can think of there as being 256 possible luminance levels (0=black, 255=white). • We can then create a drawing surface that is 256 pixels wide, and draw 256 vertical lines representing each of the possible levels of brightness. We will explore this in code on Thursday, but we can play with it in an app now…
Background image of page 6
Notes © 2005-2011 : Evan Golub (egolub@acm.org) Interpreting the Histogram • Interpreting an image’s histogram is not a straight- forward task. • It is often said that it is desirable to have:
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 8
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 01/13/2012 for the course HONR 208W taught by Professor Golub during the Fall '11 term at Maryland.

Page1 / 27

Notes060709 - Honors 208W Fall 2011 Picture of Marilyn...

This preview shows document pages 1 - 8. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online